Projeto Final
Anderson Caio Emerson Tiago Vinicius
2023-06-17
Import de pacotes utilizados
library(tidyverse)## Warning: package 'tidyverse' was built under R version 4.3.1## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr 1.1.2 ✔ readr 2.1.4
## ✔ forcats 1.0.0 ✔ stringr 1.5.0
## ✔ ggplot2 3.4.2 ✔ tibble 3.2.1
## ✔ lubridate 1.9.2 ✔ tidyr 1.3.0
## ✔ purrr 1.0.1
## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag() masks stats::lag()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errorslibrary(ggplot2)
library(summarytools)## Warning: package 'summarytools' was built under R version 4.3.1##
## Attaching package: 'summarytools'
##
## The following object is masked from 'package:tibble':
##
## viewlibrary(gmodels)## Warning: package 'gmodels' was built under R version 4.3.1library(dplyr)
library(fastDummies)## Warning: package 'fastDummies' was built under R version 4.3.1Leitura dos dados train.csv
# nao mostrar os resultados na notacao cientifica
options(scipen = 999)
library(readr)
df <- read_csv("./data/train.csv")## Rows: 24976 Columns: 108
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (7): 023c68873b, 361f93f4d1, 8d0606b150, 91145d159d, b835dfe10f, e16e6...
## dbl (101): 016399044a, 0342faceb5, 04e7268385, 06888ceac9, 072b7e8f27, 08723...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.df_test <- read_csv("./data/test.csv")## Rows: 24976 Columns: 107
## ── Column specification ────────────────────────────────────────────────────────
## Delimiter: ","
## chr (7): 023c68873b, 361f93f4d1, 8d0606b150, 91145d159d, b835dfe10f, e16e6...
## dbl (100): 016399044a, 0342faceb5, 04e7268385, 06888ceac9, 072b7e8f27, 08723...
##
## ℹ Use `spec()` to retrieve the full column specification for this data.
## ℹ Specify the column types or set `show_col_types = FALSE` to quiet this message.Os dados apresentam nomes de colunas dificeis de serem identificadas, então o primeiro passo foi converter todas as colunas das variáveis preditoras para x1,x2,x3,…,xn e criar um dicionario pra identificalas.
# Nomes das colunas que você quer renomear
colunas_para_renomear <- setdiff(names(df), c("id", "target"))
# Número de colunas para renomear
num_colunas <- length(colunas_para_renomear)
# Inicializando o dicionário
dicionario <- list()
# Renomear as colunas para x1, x2, x3, ... e criar o dicionario
for (i in 1:num_colunas) {
colname <- colunas_para_renomear[i]
new_colname <- paste("x", i, sep="")
# Adicionando ao dicionário
dicionario[[new_colname]] <- colname
print(paste(colname, "->", new_colname))
# Renomeando a coluna
names(df)[names(df) == colname] <- new_colname
}## [1] "016399044a -> x1"
## [1] "023c68873b -> x2"
## [1] "0342faceb5 -> x3"
## [1] "04e7268385 -> x4"
## [1] "06888ceac9 -> x5"
## [1] "072b7e8f27 -> x6"
## [1] "087235d61e -> x7"
## [1] "0b846350ef -> x8"
## [1] "0e2ab0831c -> x9"
## [1] "12eda2d982 -> x10"
## [1] "136c1727c3 -> x11"
## [1] "173b6590ae -> x12"
## [1] "174825d438 -> x13"
## [1] "1f222e3669 -> x14"
## [1] "1f3058af83 -> x15"
## [1] "1fa099bb01 -> x16"
## [1] "20f1afc5c7 -> x17"
## [1] "253eb5ef11 -> x18"
## [1] "25bbf0e7e7 -> x19"
## [1] "2719b72c0d -> x20"
## [1] "298ed82b22 -> x21"
## [1] "29bbd86997 -> x22"
## [1] "2a457d15d9 -> x23"
## [1] "2bc6ab42f7 -> x24"
## [1] "2d7fe4693a -> x25"
## [1] "2e874bc151 -> x26"
## [1] "361f93f4d1 -> x27"
## [1] "384bec5dd1 -> x28"
## [1] "3df2300fa2 -> x29"
## [1] "3e200bf766 -> x30"
## [1] "3eb53ae932 -> x31"
## [1] "435dec85e2 -> x32"
## [1] "4468394575 -> x33"
## [1] "49756d8e0f -> x34"
## [1] "4fc17427c8 -> x35"
## [1] "55907cc1de -> x36"
## [1] "55cf3f7627 -> x37"
## [1] "56371466d7 -> x38"
## [1] "5b862c0a8f -> x39"
## [1] "5f360995ef -> x40"
## [1] "60ec1426ce -> x41"
## [1] "63bcf89b1d -> x42"
## [1] "6516422788 -> x43"
## [1] "65aed7dc1f -> x44"
## [1] "6db53d265a -> x45"
## [1] "7734c0c22f -> x46"
## [1] "7743f273c2 -> x47"
## [1] "779d13189e -> x48"
## [1] "77b3b41efa -> x49"
## [1] "7841b6a5b1 -> x50"
## [1] "789b5244a9 -> x51"
## [1] "7925993f42 -> x52"
## [1] "7cb7913148 -> x53"
## [1] "7fe6cb4c98 -> x54"
## [1] "8311343404 -> x55"
## [1] "87b982928b -> x56"
## [1] "8a21502326 -> x57"
## [1] "8c2e088a3d -> x58"
## [1] "8d0606b150 -> x59"
## [1] "8de0382f02 -> x60"
## [1] "8f5f7c556a -> x61"
## [1] "91145d159d -> x62"
## [1] "96c30c7eef -> x63"
## [1] "96e6f0be58 -> x64"
## [1] "98475257f7 -> x65"
## [1] "99d44111c9 -> x66"
## [1] "9a575e82a4 -> x67"
## [1] "9b6e0b36c2 -> x68"
## [1] "a14fd026ce -> x69"
## [1] "a24802caa5 -> x70"
## [1] "aa69c802b6 -> x71"
## [1] "abca7a848f -> x72"
## [1] "ac826f0013 -> x73"
## [1] "ae08d2297e -> x74"
## [1] "aee1e4fc85 -> x75"
## [1] "b4112a94a6 -> x76"
## [1] "b709f75447 -> x77"
## [1] "b835dfe10f -> x78"
## [1] "b9a487ac3c -> x79"
## [1] "ba54a2a637 -> x80"
## [1] "bdf934caa7 -> x81"
## [1] "beb6e17af1 -> x82"
## [1] "c0c3df65b1 -> x83"
## [1] "c1b8ce2354 -> x84"
## [1] "c58f611921 -> x85"
## [1] "d035af6ffa -> x86"
## [1] "d2c775fa99 -> x87"
## [1] "d4d6566f9c -> x88"
## [1] "dcfcbc2ea1 -> x89"
## [1] "e0a0772df0 -> x90"
## [1] "e16e640635 -> x91"
## [1] "e5efa4d39a -> x92"
## [1] "e7ee22effb -> x93"
## [1] "e86a2190c1 -> x94"
## [1] "ea0f4a32e3 -> x95"
## [1] "ed7e658a27 -> x96"
## [1] "ee2ac696ff -> x97"
## [1] "f013b60e50 -> x98"
## [1] "f0a0febd35 -> x99"
## [1] "f1f0984934 -> x100"
## [1] "f66b98dd69 -> x101"
## [1] "fbf66c8021 -> x102"
## [1] "fdf8628ca7 -> x103"
## [1] "fe0318e273 -> x104"
## [1] "fe8cdd80ba -> x105"
## [1] "ffd1cdcfc1 -> x106"Durante nossa analise identificamos todas as variaveis qualitativas e as transformamos em variaveis do tipo factor.
df$x2 <- factor(df$x2)
df$x5 <- factor(df$x5)
df$x27 <- factor(df$x27)
df$x28 <- factor(df$x28)
df$x53 <- factor(df$x53, ordered=TRUE)
df$x59 <- factor(df$x59)
df$x62 <- factor(df$x62)
df$x67 <- factor(df$x67)
df$x78 <- factor(df$x78)
df$x91 <- factor(df$x91)
df$x100 <- factor(df$x100)5ª etapa: Faça a análise descritiva das variáveis. Apresente os gráficos e as medidas resumos.
Com as variaveis devidamente transformadas fazemos a analise descritiva:
Conhecer as variaveis
# medidas resumo
summary(df)## x1 x2 x3
## Min. :6129 369c07e037bdf9071badfa06c0f6ef4e: 59 Min. :5040
## 1st Qu.:6398 c0f379d9af329b0213f319e69a97c4a6: 57 1st Qu.:5292
## Median :6452 8f41b2d9ac870e4e2211b7f8c77b8015: 56 Median :5339
## Mean :6452 a61b6349dc22d541cb2bf767cba9a84b: 56 Mean :5339
## 3rd Qu.:6507 ce46ea842bf36508eb7405ee3241a4c5: 55 3rd Qu.:5385
## Max. :6805 58586eae2b39d07886d0906440df8c02: 54 Max. :5595
## (Other) :24639
## x4 x5 x6 x7
## Min. :35132 0: 3505 Min. :-131.5 Min. :-33.00
## 1st Qu.:35717 1:21471 1st Qu.: 279.5 1st Qu.: 10.00
## Median :35843 Median : 573.0 Median : 24.00
## Mean :35844 Mean : 789.3 Mean : 37.87
## 3rd Qu.:35971 3rd Qu.:1074.7 3rd Qu.: 65.00
## Max. :36617 Max. :7683.0 Max. :155.00
##
## x8 x9 x10 x11
## Min. :-534285.1 Min. :-4801.982 Min. : 6.357 Min. : 0.210
## 1st Qu.: -1.0 1st Qu.: -0.973 1st Qu.: 32.500 1st Qu.: 1.837
## Median : 0.0 Median : 0.008 Median : 42.081 Median : 2.707
## Mean : -21.2 Mean : -0.147 Mean : 44.045 Mean : 3.216
## 3rd Qu.: 1.0 3rd Qu.: 1.006 3rd Qu.: 53.661 3rd Qu.: 4.016
## Max. : 8511.2 Max. : 3263.127 Max. :136.076 Max. :31.790
##
## x12 x13 x14 x15
## Min. :0.2129 Min. : 4 Min. :15.23 Min. :34686
## 1st Qu.:0.8380 1st Qu.:12398 1st Qu.:21.87 1st Qu.:35379
## Median :0.9485 Median :25072 Median :28.33 Median :35506
## Mean :0.9349 Mean :25004 Mean :28.35 Mean :35507
## 3rd Qu.:1.0465 3rd Qu.:37493 3rd Qu.:34.91 3rd Qu.:35634
## Max. :1.3967 Max. :49952 Max. :41.37 Max. :36323
##
## x16 x17 x18 x19
## Min. :-64.00 Min. : 0.0002 Min. :0.0000029 Min. :-91.00
## 1st Qu.: 16.00 1st Qu.: 2.4376 1st Qu.:0.2247037 1st Qu.: 17.00
## Median : 28.00 Median : 5.8543 Median :0.4995968 Median : 23.00
## Mean : 41.42 Mean : 8.4452 Mean :0.5002357 Mean : 42.27
## 3rd Qu.: 63.00 3rd Qu.:11.7095 3rd Qu.:0.7757522 3rd Qu.: 66.00
## Max. :212.00 Max. :86.1792 Max. :0.9999775 Max. :223.00
##
## x20 x21 x22 x23
## Min. : 127.2 Min. :0.003121 Min. :0.002308 Min. :-116.00
## 1st Qu.: 15913.4 1st Qu.:0.321315 1st Qu.:0.315105 1st Qu.: 17.00
## Median : 63080.5 Median :0.503397 Median :0.495207 Median : 21.00
## Mean : 62287.1 Mean :0.500901 Mean :0.499155 Mean : 36.18
## 3rd Qu.:108226.1 3rd Qu.:0.680018 3rd Qu.:0.683253 3rd Qu.: 54.00
## Max. :123826.3 Max. :0.997309 Max. :0.999233 Max. : 212.00
##
## x24 x25 x26
## Min. : 24.66 Min. : 0.03204 Min. :0.07276
## 1st Qu.: 92.60 1st Qu.: 1.99667 1st Qu.:0.68785
## Median : 131.57 Median : 3.34972 Median :0.89379
## Mean : 173.87 Mean : 3.91553 Mean :0.89808
## 3rd Qu.: 202.79 3rd Qu.: 5.21012 3rd Qu.:1.10587
## Max. :3254.31 Max. :20.37858 Max. :2.03634
##
## x27 x28 x29
## f06a110f1992f4b2ebb6bca6a484978a: 58 0: 2897 Min. : 58.05
## ee9fc69b78ba54e1eb43e25d099bbe31: 53 1:22079 1st Qu.: 142.35
## 0be236dfcfb635f559f232d7ca65f93c: 51 Median : 206.88
## e4332210c6788b369e8cc7f54808dabb: 51 Mean : 281.52
## 61e66ed9cf26784e514e6536dbf791c5: 49 3rd Qu.: 329.49
## e55e3904c3dd4cae319de4913fad7004: 49 Max. :5538.49
## (Other) :24665
## x30 x31 x32 x33
## Min. :37674 Min. :1.538 Min. :0.0000369 Min. : 3.062
## 1st Qu.:38298 1st Qu.:2.468 1st Qu.:0.0737484 1st Qu.:13.876
## Median :38431 Median :2.715 Median :0.1794271 Median :17.680
## Mean :38431 Mean :2.743 Mean :0.2560269 Mean :18.338
## 3rd Qu.:38565 3rd Qu.:2.988 3rd Qu.:0.3522771 3rd Qu.:22.026
## Max. :39270 Max. :4.854 Max. :2.8260357 Max. :52.560
##
## x34 x35 x36 x37
## Min. :0.0004708 Min. :-29454.38 Min. : 0.00014 Min. :0.0000017
## 1st Qu.:0.3074208 1st Qu.: -0.96 1st Qu.: 2.80040 1st Qu.:1.0022405
## Median :0.4999183 Median : 0.02 Median : 6.79340 Median :1.0065804
## Mean :0.4980019 Mean : 0.22 Mean : 9.87359 Mean :0.9351881
## 3rd Qu.:0.6885438 3rd Qu.: 1.03 3rd Qu.:13.60292 3rd Qu.:1.0142407
## Max. :0.9995046 Max. : 33372.54 Max. :83.84800 Max. :1.1100283
##
## x38 x39 x40 x41
## Min. :13225 Min. :4802 Min. :431.0 Min. :0.0515
## 1st Qu.:13573 1st Qu.:5054 1st Qu.:513.0 1st Qu.:0.6988
## Median :13652 Median :5102 Median :528.0 Median :0.9324
## Mean :13652 Mean :5102 Mean :528.5 Mean :0.9420
## 3rd Qu.:13730 3rd Qu.:5150 3rd Qu.:544.0 3rd Qu.:1.1684
## Max. :14133 Max. :5389 Max. :632.0 Max. :2.3385
##
## x42 x43 x44 x45
## Min. : 0.00014 Min. : 63.28 Min. :-96.00 Min. : 12
## 1st Qu.: 1.19356 1st Qu.:202.02 1st Qu.: 17.00 1st Qu.:12626
## Median : 2.88026 Median :227.86 Median : 24.00 Median :25150
## Mean : 4.20579 Mean :235.18 Mean : 43.66 Mean :25040
## 3rd Qu.: 5.79478 3rd Qu.:263.03 3rd Qu.: 69.00 3rd Qu.:37581
## Max. :42.29624 Max. :469.58 Max. :236.00 Max. :49950
##
## x46 x47 x48 x49
## Min. :-23.49 Min. : 0.001 Min. :-11613.256 Min. :-185.790
## 1st Qu.: 25.88 1st Qu.: 1.993 1st Qu.: -0.986 1st Qu.: 2.912
## Median : 49.86 Median : 4.796 Median : 0.005 Median : 39.806
## Mean : 56.15 Mean : 6.920 Mean : 1.422 Mean : 39.999
## 3rd Qu.: 78.86 3rd Qu.: 9.653 3rd Qu.: 0.996 3rd Qu.: 77.485
## Max. :316.56 Max. :72.708 Max. : 15196.709 Max. : 253.983
##
## x50 x51 x52 x53
## Min. :-154.9 Min. :0.1356 Min. : 0.00025 1 :9175
## 1st Qu.: 928.7 1st Qu.:0.7698 1st Qu.: 1.96949 0 :8455
## Median :2189.5 Median :0.9283 Median : 4.82701 2 :4917
## Mean :2182.3 Mean :0.9157 Mean : 6.94611 3 :1830
## 3rd Qu.:3424.0 3rd Qu.:1.0711 3rd Qu.: 9.67463 4 : 481
## Max. :4508.7 Max. :1.5943 Max. :70.37153 5 : 99
## (Other): 19
## x54 x55 x56 x57
## Min. : 0.00014 Min. : 0.06004 Min. :0.0000003 Min. : 34.29
## 1st Qu.: 2.73093 1st Qu.: 2.13747 1st Qu.:0.1954873 1st Qu.: 611.57
## Median : 6.53069 Median : 4.98332 Median :0.5057884 Median : 1250.03
## Mean : 9.42799 Mean : 7.09229 Mean :0.5011737 Mean : 1652.19
## 3rd Qu.:13.12237 3rd Qu.: 9.82829 3rd Qu.:0.8036556 3rd Qu.: 2270.48
## Max. :91.36094 Max. :71.54517 Max. :0.9999999 Max. :12319.00
##
## x58 x59 x60
## Min. :47421 117cd0c0a39f9b93448f6e73302671bd: 59 Min. : 2281
## 1st Qu.:47475 fd076afc9ab10ead6bbada35a74869c5: 53 1st Qu.: 52250
## Median :47483 0f5002bbbb17df40b636a4c4c50bd710: 51 Median : 124587
## Mean :47482 76492e644fe01fb74d86d279ff588f4a: 51 Mean : 178125
## 3rd Qu.:47491 79367a94cd8ad8a1386c608d0b150d2a: 51 3rd Qu.: 247637
## Max. :47523 23ccdc7abca6c5cef5f3f5336e82116d: 50 Max. :1887315
## (Other) :24661
## x61 x62 x63
## Min. :-83.00 33073762299a55d2ab54f847c8a7c921: 66 Min. :0.000126
## 1st Qu.: 13.00 e256327c1844e3666894a63bef12f128: 63 1st Qu.:0.331263
## Median : 19.00 9af1df22f4087751f683a99501ad6b98: 60 Median :0.721685
## Mean : 37.43 254d6edd9704920df808f41b13e3549f: 59 Mean :0.968226
## 3rd Qu.: 60.00 68c724d6abd5cd93b6f531ecad977f74: 59 3rd Qu.:1.346574
## Max. :209.00 52fb248a94e8650cebfbbfb21a8b6c0b: 58 Max. :7.492790
## (Other) :24611
## x64 x65 x66 x67
## Min. : 0.05532 Min. : 0.000087 Min. :-142657715 0: 1031
## 1st Qu.: 1.44897 1st Qu.: 0.717958 1st Qu.: 28086 1:23945
## Median : 2.70032 Median : 1.742367 Median : 38516
## Mean : 4.16138 Mean : 2.529009 Mean : 33954
## 3rd Qu.: 5.10120 3rd Qu.: 3.482941 3rd Qu.: 48969
## Max. :106.57126 Max. :25.173468 Max. : 32543875
##
## x68 x69 x70 x71
## Min. :-50247.20 Min. :-54.0 Min. :-5339.624 Min. :-26342.955
## 1st Qu.: -1.01 1st Qu.: 13.0 1st Qu.: -1.038 1st Qu.: -0.996
## Median : -0.01 Median : 25.0 Median : -0.009 Median : -0.002
## Mean : -2.13 Mean : 39.4 Mean : 0.734 Mean : -0.750
## 3rd Qu.: 0.98 3rd Qu.: 65.0 3rd Qu.: 0.992 3rd Qu.: 0.984
## Max. : 3400.30 Max. :216.0 Max. :28989.428 Max. : 8367.628
##
## x72 x73 x74 x75
## Min. : 4 Min. :0.9085 Min. : 1 Min. :0.0000
## 1st Qu.:12618 1st Qu.:2.3719 1st Qu.:12298 1st Qu.:0.1415
## Median :25091 Median :2.8712 Median :24920 Median :0.4902
## Mean :25035 Mean :2.9878 Mean :24867 Mean :0.4971
## 3rd Qu.:37528 3rd Qu.:3.4751 3rd Qu.:37432 3rd Qu.:0.8536
## Max. :49951 Max. :9.8836 Max. :49952 Max. :1.0000
##
## x76 x77
## Min. : 0.000428 Min. :-40148.62
## 1st Qu.: 0.801365 1st Qu.: -0.98
## Median : 1.962001 Median : 0.02
## Mean : 2.821592 Mean : 1.52
## 3rd Qu.: 3.937126 3rd Qu.: 1.01
## Max. :30.254508 Max. : 84416.90
##
## x78 x79 x80
## c6f6b3061e7ee6f986caf12f7beef509: 224 Min. :0.08084 Min. :-68361.97
## 673390b6aa6ebef46d851ebbfd7c19a6: 221 1st Qu.:0.74711 1st Qu.: -1.01
## 68ab2c192c6fd62d9de503be78cbd3fe: 219 Median :0.91691 Median : -0.01
## 34b29495d27155762785160c1d44beaa: 215 Mean :0.90959 Mean : -1.84
## 4661209cb3adaa375abf500a72b87574: 214 3rd Qu.:1.07929 3rd Qu.: 1.00
## 9a2d2cb82d158f83ab721a316c899698: 209 Max. :1.74156 Max. : 33213.56
## (Other) :23674
## x81 x82 x83 x84
## Min. : 0.0798 Min. : 1 Min. : 1 Min. : 45778999
## 1st Qu.: 1.5496 1st Qu.:12748 1st Qu.:12895 1st Qu.: 73438011
## Median : 2.7376 Median :25322 Median :25340 Median : 80764553
## Mean : 3.9679 Mean :25167 Mean :25232 Mean : 81618138
## 3rd Qu.: 4.8719 3rd Qu.:37621 3rd Qu.:37691 3rd Qu.: 88890375
## Max. :67.1302 Max. :49952 Max. :49952 Max. :144378835
##
## x85 x86 x87 x88
## Min. :-13521.150 Min. :-1269 Min. :2776 Min. : 670
## 1st Qu.: -0.983 1st Qu.: 1532 1st Qu.:2941 1st Qu.: 164445
## Median : 0.006 Median : 1984 Median :2975 Median : 397960
## Mean : -0.426 Mean : 1987 Mean :2976 Mean : 567152
## 3rd Qu.: 0.992 3rd Qu.: 2446 3rd Qu.:3010 3rd Qu.: 779489
## Max. : 3080.032 Max. :13949 Max. :3179 Max. :6244488
##
## x89 x90 x91
## Min. :38744 Min. :0.0000011 dfaeacc0ced1ca04fc8e0815cdb78525: 184
## 1st Qu.:39349 1st Qu.:0.2103642 f949431d6f18e3b26f6fde1b20f070ec: 184
## Median :39487 Median :0.5020075 876b7bc4a2ec297062ee531d9ba4a24f: 179
## Mean :39485 Mean :0.5007384 250e6488c3a4b403cadb87b2866a50d8: 174
## 3rd Qu.:39619 3rd Qu.:0.7893820 515ac2ee6867f341f68fa79372d17679: 174
## Max. :40304 Max. :0.9999998 3e1273ad0cf5a5f27270b9540e046211: 171
## (Other) :23910
## x92 x93 x94 x95
## Min. : -129.3 Min. :-56.0 Min. : 1 Min. :0.1411
## 1st Qu.:13909.5 1st Qu.: 13.0 1st Qu.:12395 1st Qu.:0.7995
## Median :21861.3 Median : 21.0 Median :24977 Median :0.9369
## Mean :22035.8 Mean : 32.8 Mean :24912 Mean :0.9254
## 3rd Qu.:30173.5 3rd Qu.: 51.0 3rd Qu.:37442 3rd Qu.:1.0612
## Max. :46660.3 Max. :158.0 Max. :49952 Max. :1.5225
##
## x96 x97 x98 x99
## Min. : 2514 Min. :0.001317 Min. :0.2541 Min. :-188.18
## 1st Qu.:10312 1st Qu.:1.003929 1st Qu.:0.8434 1st Qu.: 25.61
## Median :13186 Median :1.005198 Median :0.9534 Median : 69.13
## Mean :14843 Mean :0.968233 Mean :0.9380 Mean : 69.24
## 3rd Qu.:17814 3rd Qu.:1.006697 3rd Qu.:1.0466 3rd Qu.: 112.90
## Max. :62001 Max. :1.017143 Max. :1.3503 Max. : 311.19
##
## x100 x101 x102
## 6f2a574469db65c13448b693ad5aca1c: 106 Min. :0.0000022 Min. :-101.38
## ac57568a3a435501ac356cad77a4d957: 103 1st Qu.:0.1444816 1st Qu.: 17.06
## 7d1ab1e7b26fcbd91a972154f6fa860e: 100 Median :0.5829451 Median : 40.68
## b1d448724055697b94a122878757a54a: 100 Mean :0.5755702 Mean : 40.71
## c0e421345f4d099c646992fad48af409: 97 3rd Qu.:1.0025573 3rd Qu.: 64.86
## dd19fd8cab2ba69b1d2271cbd0817ca0: 97 Max. :1.1458164 Max. : 179.20
## (Other) :24373
## x103 x104 x105 x106
## Min. : 846.0 Min. :0.000259 Min. : 0.236 Min. : 0.3315
## 1st Qu.: 977.0 1st Qu.:1.000519 1st Qu.:14.890 1st Qu.: 1.8503
## Median : 997.0 Median :1.000597 Median :26.957 Median : 2.6993
## Mean : 996.9 Mean :0.973738 Mean :27.027 Mean : 3.1630
## 3rd Qu.:1017.0 3rd Qu.:1.000674 3rd Qu.:39.215 3rd Qu.: 3.9484
## Max. :1111.0 Max. :1.001109 Max. :61.403 Max. :24.3726
##
## id target
## Min. : 0 Min. :-0.2398
## 1st Qu.: 6244 1st Qu.: 0.5031
## Median :12488 Median : 0.9838
## Mean :12488 Mean : 1.6609
## 3rd Qu.:18731 3rd Qu.: 1.9680
## Max. :24975 Max. :61.3261
## Grafico univariado da target
# grafico de uma variavel
qplot(x=df$target)## Warning: `qplot()` was deprecated in ggplot2 3.4.0.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
Separamos as variaveis quantitativas, qualitativas e a variavel target para fazermos manipulações de maneira mais facil
dadosQuali <- df %>%
select(x2,x5,x27,x28,x53,x59,x62,x67,x78,x91,x100)
dadosQuant <- df %>%
select(-c(id,target,x2,x5,x27,x28,x53,x59,x62,x67,x78,x91,x100))
target <- df$targetAnálise bivariada das variáveis qualitativas
# Gráficos de barras para x2 e x5
barplot(table(df$x2), main="Gráfico de barras de x2", xlab="x2")
barplot(table(df$x5), main="Gráfico de barras de x5", xlab="x5")
barplot(table(df$x27), main="Gráfico de barras de x27", xlab="x27")
barplot(table(df$x28), main="Gráfico de barras de x28", xlab="x28")
barplot(table(df$x53), main="Gráfico de barras de x53", xlab="x53")
barplot(table(df$x59), main="Gráfico de barras de x59", xlab="x59")
barplot(table(df$x62), main="Gráfico de barras de x62", xlab="x62")
barplot(table(df$x67), main="Gráfico de barras de x67", xlab="x67")
barplot(table(df$x78), main="Gráfico de barras de x78", xlab="x78")
barplot(table(df$x91), main="Gráfico de barras de x91", xlab="x91")
barplot(table(df$x100), main="Gráfico de barras de x100", xlab="x100")
6ª etapa: Faça a análise bivariada das variáveis qualitativas.
a) Tabela de frequência bivariada
b) Teste Qui-quadrado.
Analise da variavel target vs x53, x5, x28 e x67
Primeiro passo: transformar a variavel quantitativa (target) em uma qualitativa (faixa de target)
Criterio: fórmula de Sturges
# Calcular o número de bins usando a fórmula de Sturges
n <- length(df$target)
k <- round(1 + 3.322 * log10(n))Para análise bivariada das variáveis qualitativas criamos as faixas de valores para variavel target.
# Criar a variável faixa de target
df1 <- df
# Usando cut para criar as faixas e labels apropriadas
df1$fxtarget_cat <- cut(df$target, breaks = k, include.lowest = TRUE, dig.lab = 10)
# Converter para um fator ordenado
df1$fxtarget_cat <- factor(df1$fxtarget_cat, ordered = TRUE)
# Mostrando as frequências das faixas
freq(df1$fxtarget_cat)## Frequencies
## df1$fxtarget_cat
## Type: Ordered Factor
##
## Freq % Valid % Valid Cum. % Total % Total Cum.
## --------------------------------- ------- --------- -------------- --------- --------------
## [-0.3014040834,3.608034849] 22429 89.802 89.802 89.802 89.802
## (3.608034849,7.455907814] 1953 7.820 97.622 7.820 97.622
## (7.455907814,11.30378078] 397 1.590 99.211 1.590 99.211
## (11.30378078,15.15165374] 105 0.420 99.632 0.420 99.632
## (15.15165374,18.99952671] 40 0.160 99.792 0.160 99.792
## (18.99952671,22.84739967] 25 0.100 99.892 0.100 99.892
## (22.84739967,26.69527264] 13 0.052 99.944 0.052 99.944
## (26.69527264,30.5431456] 2 0.008 99.952 0.008 99.952
## (30.5431456,34.39101857] 2 0.008 99.960 0.008 99.960
## (34.39101857,38.23889153] 3 0.012 99.972 0.012 99.972
## (38.23889153,42.0867645] 2 0.008 99.980 0.008 99.980
## (42.0867645,45.93463746] 1 0.004 99.984 0.004 99.984
## (45.93463746,49.78251043] 3 0.012 99.996 0.012 99.996
## (57.47825636,61.38769529] 1 0.004 100.000 0.004 100.000
## <NA> 0 0.000 100.000
## Total 24976 100.000 100.000 100.000 100.000Temos uma tabela de frequência bivariada que compara duas variáveis categóricas e tambem ja nos apresenta o teste Qui-quadrado como output.
Statistics for All Table Factors: Nesta seção, temos o resultado do teste qui-quadrado de Pearson que testa a independência entre as duas variáveis categóricas.
- Chi^2: O valor da estatística qui-quadrado.
- d.f.: Os graus de liberdade para o teste.
- p: O valor-p associado ao teste qui-quadrado. quando este valor é extremamente próximo de 0, sugere que podemos rejeitar a hipótese nula de que as duas variáveis são independentes.
df1$quali_x53 <- factor(df1$x53)
CrossTable(df1$fxtarget_cat,df1$quali_x53, prop.r = FALSE, prop.c = FALSE, prop.t = FALSE,
prop.chisq = FALSE,chisq = TRUE)## Warning in chisq.test(t, correct = FALSE, ...): Aproximação do qui-quadrado
## pode estar incorreta##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 24976
##
##
## | df1$quali_x53
## df1$fxtarget_cat | 0 | 1 | 2 | 3 | 4 | 5 | 6 | 7 | Row Total |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## [-0.3014040834,3.608034849] | 7602 | 8249 | 4409 | 1640 | 423 | 89 | 15 | 2 | 22429 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (3.608034849,7.455907814] | 657 | 708 | 381 | 152 | 44 | 9 | 2 | 0 | 1953 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (7.455907814,11.30378078] | 129 | 139 | 91 | 28 | 10 | 0 | 0 | 0 | 397 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (11.30378078,15.15165374] | 46 | 36 | 14 | 7 | 1 | 1 | 0 | 0 | 105 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (15.15165374,18.99952671] | 13 | 16 | 7 | 2 | 2 | 0 | 0 | 0 | 40 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (18.99952671,22.84739967] | 5 | 12 | 7 | 0 | 1 | 0 | 0 | 0 | 25 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (22.84739967,26.69527264] | 2 | 9 | 2 | 0 | 0 | 0 | 0 | 0 | 13 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (26.69527264,30.5431456] | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 2 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (30.5431456,34.39101857] | 0 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 2 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (34.39101857,38.23889153] | 1 | 0 | 2 | 0 | 0 | 0 | 0 | 0 | 3 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (38.23889153,42.0867645] | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 2 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (42.0867645,45.93463746] | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (45.93463746,49.78251043] | 0 | 2 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## (57.47825636,61.38769529] | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
## Column Total | 8455 | 9175 | 4917 | 1830 | 481 | 99 | 17 | 2 | 24976 |
## ----------------------------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 56.49066 d.f. = 91 p = 0.9982963
##
##
## df1$quali_x5 <- factor(df1$x5)
CrossTable(df1$fxtarget_cat,df1$quali_x5, prop.r = FALSE, prop.c = FALSE, prop.t = FALSE,
prop.chisq = FALSE,chisq = TRUE)## Warning in chisq.test(t, correct = FALSE, ...): Aproximação do qui-quadrado
## pode estar incorreta##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 24976
##
##
## | df1$quali_x5
## df1$fxtarget_cat | 0 | 1 | Row Total |
## ----------------------------|-----------|-----------|-----------|
## [-0.3014040834,3.608034849] | 2901 | 19528 | 22429 |
## ----------------------------|-----------|-----------|-----------|
## (3.608034849,7.455907814] | 446 | 1507 | 1953 |
## ----------------------------|-----------|-----------|-----------|
## (7.455907814,11.30378078] | 96 | 301 | 397 |
## ----------------------------|-----------|-----------|-----------|
## (11.30378078,15.15165374] | 32 | 73 | 105 |
## ----------------------------|-----------|-----------|-----------|
## (15.15165374,18.99952671] | 12 | 28 | 40 |
## ----------------------------|-----------|-----------|-----------|
## (18.99952671,22.84739967] | 8 | 17 | 25 |
## ----------------------------|-----------|-----------|-----------|
## (22.84739967,26.69527264] | 4 | 9 | 13 |
## ----------------------------|-----------|-----------|-----------|
## (26.69527264,30.5431456] | 2 | 0 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (30.5431456,34.39101857] | 2 | 0 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (34.39101857,38.23889153] | 2 | 1 | 3 |
## ----------------------------|-----------|-----------|-----------|
## (38.23889153,42.0867645] | 0 | 2 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (42.0867645,45.93463746] | 0 | 1 | 1 |
## ----------------------------|-----------|-----------|-----------|
## (45.93463746,49.78251043] | 0 | 3 | 3 |
## ----------------------------|-----------|-----------|-----------|
## (57.47825636,61.38769529] | 0 | 1 | 1 |
## ----------------------------|-----------|-----------|-----------|
## Column Total | 3505 | 21471 | 24976 |
## ----------------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 256.037 d.f. = 13 p = 0.00000000000000000000000000000000000000000000003564283
##
##
## df1$quali_x28 <- factor(df1$x28)
CrossTable(df1$fxtarget_cat,df1$quali_x28, prop.r = FALSE, prop.c = FALSE, prop.t = FALSE,
prop.chisq = FALSE,chisq = TRUE)## Warning in chisq.test(t, correct = FALSE, ...): Aproximação do qui-quadrado
## pode estar incorreta##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 24976
##
##
## | df1$quali_x28
## df1$fxtarget_cat | 0 | 1 | Row Total |
## ----------------------------|-----------|-----------|-----------|
## [-0.3014040834,3.608034849] | 2618 | 19811 | 22429 |
## ----------------------------|-----------|-----------|-----------|
## (3.608034849,7.455907814] | 222 | 1731 | 1953 |
## ----------------------------|-----------|-----------|-----------|
## (7.455907814,11.30378078] | 37 | 360 | 397 |
## ----------------------------|-----------|-----------|-----------|
## (11.30378078,15.15165374] | 12 | 93 | 105 |
## ----------------------------|-----------|-----------|-----------|
## (15.15165374,18.99952671] | 3 | 37 | 40 |
## ----------------------------|-----------|-----------|-----------|
## (18.99952671,22.84739967] | 1 | 24 | 25 |
## ----------------------------|-----------|-----------|-----------|
## (22.84739967,26.69527264] | 2 | 11 | 13 |
## ----------------------------|-----------|-----------|-----------|
## (26.69527264,30.5431456] | 0 | 2 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (30.5431456,34.39101857] | 1 | 1 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (34.39101857,38.23889153] | 1 | 2 | 3 |
## ----------------------------|-----------|-----------|-----------|
## (38.23889153,42.0867645] | 0 | 2 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (42.0867645,45.93463746] | 0 | 1 | 1 |
## ----------------------------|-----------|-----------|-----------|
## (45.93463746,49.78251043] | 0 | 3 | 3 |
## ----------------------------|-----------|-----------|-----------|
## (57.47825636,61.38769529] | 0 | 1 | 1 |
## ----------------------------|-----------|-----------|-----------|
## Column Total | 2897 | 22079 | 24976 |
## ----------------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 9.918561 d.f. = 13 p = 0.7005799
##
##
## df1$quali_x67 <- factor(df1$x67)
CrossTable(df1$fxtarget_cat,df1$quali_x67, prop.r = FALSE, prop.c = FALSE, prop.t = FALSE,
prop.chisq = FALSE,chisq = TRUE)## Warning in chisq.test(t, correct = FALSE, ...): Aproximação do qui-quadrado
## pode estar incorreta##
##
## Cell Contents
## |-------------------------|
## | N |
## |-------------------------|
##
##
## Total Observations in Table: 24976
##
##
## | df1$quali_x67
## df1$fxtarget_cat | 0 | 1 | Row Total |
## ----------------------------|-----------|-----------|-----------|
## [-0.3014040834,3.608034849] | 764 | 21665 | 22429 |
## ----------------------------|-----------|-----------|-----------|
## (3.608034849,7.455907814] | 185 | 1768 | 1953 |
## ----------------------------|-----------|-----------|-----------|
## (7.455907814,11.30378078] | 52 | 345 | 397 |
## ----------------------------|-----------|-----------|-----------|
## (11.30378078,15.15165374] | 14 | 91 | 105 |
## ----------------------------|-----------|-----------|-----------|
## (15.15165374,18.99952671] | 6 | 34 | 40 |
## ----------------------------|-----------|-----------|-----------|
## (18.99952671,22.84739967] | 4 | 21 | 25 |
## ----------------------------|-----------|-----------|-----------|
## (22.84739967,26.69527264] | 3 | 10 | 13 |
## ----------------------------|-----------|-----------|-----------|
## (26.69527264,30.5431456] | 0 | 2 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (30.5431456,34.39101857] | 0 | 2 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (34.39101857,38.23889153] | 1 | 2 | 3 |
## ----------------------------|-----------|-----------|-----------|
## (38.23889153,42.0867645] | 0 | 2 | 2 |
## ----------------------------|-----------|-----------|-----------|
## (42.0867645,45.93463746] | 1 | 0 | 1 |
## ----------------------------|-----------|-----------|-----------|
## (45.93463746,49.78251043] | 1 | 2 | 3 |
## ----------------------------|-----------|-----------|-----------|
## (57.47825636,61.38769529] | 0 | 1 | 1 |
## ----------------------------|-----------|-----------|-----------|
## Column Total | 1031 | 23945 | 24976 |
## ----------------------------|-----------|-----------|-----------|
##
##
## Statistics for All Table Factors
##
##
## Pearson's Chi-squared test
## ------------------------------------------------------------
## Chi^2 = 342.7846 d.f. = 13 p = 0.00000000000000000000000000000000000000000000000000000000000000002553164
##
##
## c) Gráfico 100% empilhado
ggplot(df1, aes(fill = fxtarget_cat, x = quali_x53)) +
geom_bar(position = "fill") +
geom_text(
aes(label = paste0(round(100 * ..count../sum(..count..), 2), "%"),
y = ..count..),
position = position_fill(vjust = 0.5),
stat = "count",
size = 3,
color = "white" # Definir a cor do label como branca
) +
labs(y = "Porcentagem", x = "Quali x53", title = "Gráfico 100% Empilhado de target_cat por x53") +
scale_y_continuous(labels = scales::percent_format(scale = 1))## Warning: The dot-dot notation (`..count..`) was deprecated in ggplot2 3.4.0.
## ℹ Please use `after_stat(count)` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.
ggplot(df1, aes(fill = fxtarget_cat, x = quali_x5)) +
geom_bar(position = "fill") +
geom_text(
aes(label = paste0(round(100 * ..count../sum(..count..), 2), "%"),
y = ..count..),
position = position_fill(vjust = 0.5),
stat = "count",
size = 3,
color = "white" # Definir a cor do label como branca
) +
labs(y = "Porcentagem", x = "Quali x53", title = "Gráfico 100% Empilhado de target_cat por x5") +
scale_y_continuous(labels = scales::percent_format(scale = 1))
7ª etapa: Faça a análise bivariada das variáveis quantitativas.
d) Gráfico de dispersão.
e) Análise de correlação de Pearson.
f) Matriz de correlação de Pearson.
Selecionando as top 10 variaveis preditoras para fazermos a análise bivariada das variáveis quantitativas utilizando a correlação de pearson
1º passo - Aplicar correlação de pearson nas variaveis quantitativas
df_quant_corr <- cbind(dadosQuant,target)
# Calculando a matriz de correlação de pearson
correlacao <- cor(df_quant_corr)
correlacao## x1 x3 x4 x6 x7
## x1 1.0000000000 -0.00083219632 -0.00362479700 0.00199838602 0.0028089243
## x3 -0.0008321963 1.00000000000 0.00627263921 -0.00081013030 0.0091031298
## x4 -0.0036247970 0.00627263921 1.00000000000 0.00146660914 -0.0023005368
## x6 0.0019983860 -0.00081013030 0.00146660914 1.00000000000 0.0022673949
## x7 0.0028089243 0.00910312981 -0.00230053677 0.00226739489 1.0000000000
## x8 0.0058303507 -0.01031894992 0.00344574308 0.00582030560 0.0061009924
## x9 0.0024651174 -0.00546138311 0.01061788503 -0.00422931570 -0.0025005462
## x10 -0.0037266397 0.00090180640 0.00130062226 -0.00129718168 -0.0010237875
## x11 -0.0033185100 0.00359563871 -0.00622220421 0.00766263402 0.0006392020
## x12 0.0017334340 0.00335712242 0.00124322832 0.00356007074 -0.0048957993
## x13 -0.0048429058 0.00291910479 0.00185808594 0.01003167317 -0.0031020999
## x14 -0.0031592557 0.00291479485 -0.00060999214 0.00164728295 0.0011078452
## x15 0.0087029717 -0.00253574463 0.00656057443 -0.00385156004 -0.0009946081
## x16 -0.0026129316 -0.00085469888 -0.00846812188 0.01027634463 -0.0066364170
## x17 0.0064194441 0.00149756682 0.01882696154 -0.00408380524 -0.0031591711
## x18 0.0028937059 0.00448555550 0.00560162804 -0.00348441226 0.0071568133
## x19 0.0028082615 -0.00195504806 -0.00115351328 -0.00104805847 0.0018822566
## x20 0.0057289612 0.00259374993 0.00112493125 -0.00666635693 -0.0017374790
## x21 0.0047423092 0.01239413599 -0.00391290290 0.00131346254 0.0007169492
## x22 -0.0058827060 0.00612078195 -0.00761404787 -0.00401684403 0.0041344506
## x23 -0.0061896136 -0.00005792338 0.00458324444 -0.00562415551 -0.0058698120
## x24 -0.0002203695 0.00484423173 0.01128506859 -0.00903475339 -0.0019424113
## x25 -0.0036067783 0.00752843096 0.00166971366 -0.00066500951 0.0043411741
## x26 0.0012518589 -0.00585656119 0.00899493339 -0.00120782964 0.0032270733
## x29 0.0005066590 0.00476336894 0.01254974589 -0.00987849209 -0.0011122079
## x30 0.0030276575 0.01156027986 0.00331419567 -0.00849517747 -0.0006882836
## x31 -0.0105299159 0.00316764503 -0.00427040158 -0.00587380455 -0.0019897275
## x32 -0.0017018957 -0.01432675762 0.00687147612 -0.00258206573 -0.0120071366
## x33 0.0015594929 -0.00192916099 0.00485118596 -0.00762862403 0.0108756154
## x34 -0.0043271956 -0.00438263283 -0.00369881624 0.00102668094 -0.0087871335
## x35 0.0030861424 -0.00731974888 0.00642468350 0.00618238693 0.0037799867
## x36 -0.0057834856 -0.00617745174 -0.00209803840 -0.01294148012 -0.0027152813
## x37 -0.0038567059 -0.01667736322 -0.00061121081 0.00292983724 -0.0025724177
## x38 -0.0047064913 -0.00687030323 0.01053317568 -0.00584730647 -0.0070920808
## x39 0.0007501352 0.00731173328 -0.00501113551 0.00053865991 -0.0012461480
## x40 -0.0004712121 0.00149121452 -0.00163135686 -0.00267517556 -0.0041827497
## x41 -0.0081490900 0.00302520230 0.00681793528 0.00509249116 -0.0021779142
## x42 0.0096952020 0.00587504117 0.00781430918 -0.00316904057 -0.0055398866
## x43 -0.0070989420 0.00391585764 -0.00870461325 0.00188342813 -0.0018347085
## x44 -0.0021458687 -0.00962862551 0.01009667750 -0.00199003249 -0.0089707736
## x45 -0.0095553589 -0.00391418842 0.00288566962 0.01341941593 -0.0019325636
## x46 -0.0085043594 -0.00249122875 -0.00528315501 0.00485783143 0.0052425420
## x47 0.0005812961 -0.00446544041 -0.00649489897 -0.00515011171 0.0060255001
## x48 0.0100849628 -0.00256809561 0.00032147208 0.00210038415 0.0064457949
## x49 0.0015140765 0.00758743852 0.00183465766 -0.00357327579 -0.0024916693
## x50 0.0062819868 -0.01397476979 0.00759948479 -0.00257815497 0.0107773552
## x51 -0.0047301171 -0.00156844621 0.00257209023 0.00495487511 0.0096552157
## x52 -0.0092384744 -0.00191083105 0.00112203717 0.00479457125 0.0025410809
## x54 -0.0046617338 0.01707487458 0.00539922625 0.00975555273 -0.0035757139
## x55 -0.0017328745 -0.00306141276 0.00694291311 -0.00196184846 0.0025064270
## x56 0.0062506583 0.00113803526 -0.00089137983 0.00306667553 0.0061067021
## x57 -0.0078977906 0.00310681189 0.00308488087 0.00138667722 0.0045162741
## x58 0.0040286949 -0.01902984941 -0.00306430871 0.01300123345 0.0004124984
## x60 0.0026488090 -0.00054310270 0.00163837060 0.99581928855 0.0025788790
## x61 -0.0017207555 -0.00123683271 0.00226688444 -0.00077332998 0.0028414114
## x63 -0.0078707725 0.00292467260 0.00293334504 0.00151461976 0.0043983755
## x64 0.0003431034 0.00462976935 0.01268519951 -0.00937156211 -0.0011540880
## x65 -0.0043390144 -0.00785932446 -0.00227832058 -0.00160394689 0.0037192971
## x66 0.0061586959 -0.00391210183 0.00149063240 0.00638709502 0.0081809790
## x68 0.0109842814 -0.00761826932 -0.00600167922 0.00397322758 -0.0096067380
## x69 0.0045131799 -0.00265077468 -0.00115244285 0.00004729663 0.0139431388
## x70 -0.0034606680 0.00687152651 0.01138205745 -0.00129119082 0.0035553014
## x71 -0.0043932075 0.00712128087 -0.00719855514 0.00585647049 0.0045342360
## x72 0.0028523428 -0.01299732440 -0.00558285124 0.00555791202 -0.0069774325
## x73 -0.0042772364 0.00230834193 -0.00893109681 -0.00427629363 -0.0033298162
## x74 -0.0088874040 -0.00478557221 0.00121135553 -0.00258966068 -0.0025811616
## x75 -0.0102223241 -0.00283551674 0.00290804884 0.00848067461 0.0038348966
## x76 0.0026442500 -0.00054207752 0.00164049728 0.99581913293 0.0025772145
## x77 0.0073603837 -0.01069883049 0.00126985675 -0.00086580125 0.0007590789
## x79 -0.0063228752 -0.00490190023 0.00007580089 0.00416514940 0.0045662156
## x80 0.0003371300 -0.00319982553 -0.00801282265 -0.00470130297 -0.0002906428
## x81 -0.0028922159 0.00134155101 -0.01148285513 0.01484782057 0.0077728785
## x82 -0.0054231349 -0.01233812111 -0.00087689755 -0.00461983861 -0.0037080706
## x83 -0.0038175198 -0.00210767433 -0.00002180066 0.00235109464 -0.0053446871
## x84 -0.0105298658 0.00316768713 -0.00427039793 -0.00587380655 -0.0019897981
## x85 0.0061573566 -0.00391334125 0.00149053248 0.00638621373 0.0081801125
## x86 -0.0014753480 0.00104551514 -0.00005760458 0.00010687579 0.0023137820
## x87 -0.0054446487 0.00096769610 0.00521787983 0.00810369763 -0.0117025129
## x88 -0.0017008055 -0.01433240352 0.00687958752 -0.00258353098 -0.0120048880
## x89 0.0026561855 0.00863581368 -0.00677033369 -0.00599869349 0.0015188654
## x90 0.0062374846 -0.01368948264 0.00760008336 -0.00283078981 0.0109571364
## x92 -0.0057566474 0.00593446943 -0.00745757803 -0.00405367108 0.0041634859
## x93 0.0018367363 -0.00279653555 -0.00854515095 -0.00524413375 -0.0013624711
## x94 -0.0071169177 0.01155603700 0.00101269748 0.00502279765 0.0124609783
## x95 -0.0093356843 0.01074856491 0.00388342212 -0.00177863205 -0.0057805945
## x96 -0.0089307845 0.00255692849 0.00366649667 0.00267579118 0.0069096601
## x97 0.0148930101 -0.00086653066 0.00054274534 -0.00375402551 -0.0139560257
## x98 0.0011519440 -0.00132830396 -0.00533495149 0.00223294440 0.0001710532
## x99 0.0094124248 -0.00488992887 -0.00265424680 -0.00877838512 0.0032410882
## x101 0.0057470328 0.00259085100 0.00112064726 -0.00665860071 -0.0017470265
## x102 0.0052599698 -0.00046195183 0.01116740754 -0.00664199050 0.0103721065
## x103 0.0084329252 0.01012124310 -0.00017890514 0.00384052811 0.0093300214
## x104 -0.0006424986 -0.01144795408 0.00880994222 0.00264747022 0.0006673214
## x105 0.0028723648 0.00465596902 0.00595745474 -0.00284199294 0.0086189142
## x106 -0.0044689454 0.00507840947 0.00579890167 -0.00165110805 -0.0070566240
## target -0.0270287199 0.00344022039 -0.01353732034 -0.00489291331 0.0379737970
## x8 x9 x10 x11
## x1 0.005830350657 0.00246511743 -0.00372663973 -0.00331851001
## x3 -0.010318949925 -0.00546138311 0.00090180640 0.00359563871
## x4 0.003445743076 0.01061788503 0.00130062226 -0.00622220421
## x6 0.005820305600 -0.00422931570 -0.00129718168 0.00766263402
## x7 0.006100992351 -0.00250054618 -0.00102378746 0.00063920202
## x8 1.000000000000 0.00007731053 -0.00386877905 0.00037923759
## x9 0.000077310527 1.00000000000 0.00233390346 -0.00091499201
## x10 -0.003868779046 0.00233390346 1.00000000000 0.00078042082
## x11 0.000379237591 -0.00091499201 0.00078042082 1.00000000000
## x12 -0.009975825489 0.00574413657 0.00113574213 0.00701796252
## x13 -0.001574463734 0.00561597990 -0.00555813633 0.00820356275
## x14 -0.010680255948 0.00709476205 0.00207600083 0.01611755957
## x15 0.001812883134 -0.00319062519 0.00290787947 0.00110193205
## x16 -0.010526089096 -0.00296753924 0.00351855967 0.00075872277
## x17 -0.003207388022 0.00153258038 0.00194407172 -0.00533407396
## x18 0.001887464076 -0.00569696291 -0.00017984317 0.00452033685
## x19 0.003072181907 0.00324693136 0.01048793666 0.00106954148
## x20 0.002812180513 0.00058659698 0.01581663028 -0.00115626477
## x21 0.011469130683 0.01001349752 0.00247241305 -0.00584586132
## x22 0.006813752426 0.00762359842 -0.00076260348 0.01384420948
## x23 -0.008675532622 0.00002387407 0.00708747347 -0.01033570614
## x24 -0.008340042268 -0.00193443247 -0.00011552833 0.01099856416
## x25 0.002738284457 0.01132818661 0.00456614710 0.00319965639
## x26 -0.004047561826 -0.00022638547 -0.00366023293 -0.00342579595
## x29 -0.008719403982 -0.00212831987 -0.00066434159 0.01035857076
## x30 -0.005029038652 -0.00015246098 0.00406267604 0.00208172400
## x31 0.006653833629 -0.00125836727 0.00353363849 0.00483119350
## x32 0.006330461468 -0.00815715849 -0.00301462122 -0.01031133648
## x33 -0.015709310093 0.00214095233 0.00678653443 0.00725741256
## x34 0.001016284834 -0.00563710445 0.00035578541 0.00789043211
## x35 0.000057891208 -0.00040516795 0.00225957394 0.00212935955
## x36 -0.005353303847 -0.00051737219 0.00265553897 -0.01091952915
## x37 -0.002043625979 -0.00272613564 0.01279676523 -0.00105554849
## x38 -0.002343033344 -0.00187239938 -0.00620068639 0.00109635942
## x39 -0.007362154016 -0.00276820928 0.00036323713 0.00251832330
## x40 -0.000520798780 -0.01201003331 -0.00320717586 -0.00101335155
## x41 -0.000256317384 0.01529308172 -0.00200570674 -0.00610258757
## x42 0.003110558538 -0.00077630966 -0.00775536609 -0.01106435195
## x43 0.007167571050 0.00156869006 -0.00515905191 0.00615379128
## x44 0.004992579396 -0.00063887230 0.00482960117 -0.00328484880
## x45 -0.010923297536 0.00148321766 -0.00700192330 -0.00238498939
## x46 -0.017318633553 0.00710318314 -0.00155244427 -0.00264596650
## x47 0.001081841421 0.01897438071 -0.00085325787 -0.00432683482
## x48 -0.000337647239 -0.00048540897 0.00576028324 0.00089439673
## x49 -0.003635405443 0.00650956802 -0.00225025078 0.01178426610
## x50 0.009622798143 -0.00211033462 -0.00164789092 -0.00342423801
## x51 0.003422034414 0.00515630233 -0.00210477911 0.00470009117
## x52 -0.018876754444 0.00598237850 0.00489843011 -0.00132481520
## x54 0.006108779819 -0.00593664661 0.00300814647 -0.01108918586
## x55 -0.002141618260 -0.01005847372 0.00324657467 0.00355754678
## x56 -0.003992053386 -0.00349499451 -0.00971700379 0.00001637142
## x57 0.004319636615 0.00066846616 0.00295127074 -0.00027713756
## x58 0.002740323332 -0.00442853221 -0.00023051094 0.00003289313
## x60 0.005769517252 -0.00399893844 -0.00242261189 0.00781316454
## x61 0.004886082215 0.00284786458 0.00193217240 0.00241557396
## x63 0.004345173107 0.00058874747 0.00295235891 -0.00028970834
## x64 -0.008780385258 -0.00230475734 -0.00038492634 0.01062748109
## x65 0.005518412515 0.00696772146 0.00612135496 0.00294026791
## x66 0.000021471898 0.00058910461 0.00917187599 -0.00549954120
## x68 -0.000118210522 -0.00021447004 0.00159624714 -0.01806365826
## x69 -0.004454458867 -0.00176221816 0.00250678010 0.00672686153
## x70 0.000008868438 -0.00079850554 -0.00353761363 0.01617801732
## x71 -0.000030141973 -0.00015233168 0.00363512566 -0.00289532281
## x72 -0.001831279956 0.00337751399 0.00991514707 0.00891887241
## x73 -0.008374250907 -0.00420206625 -0.00733445543 0.00141912118
## x74 -0.002624124562 -0.00509688628 -0.00904985235 0.01087375848
## x75 -0.007375458492 0.00142208124 0.00075909555 -0.00352096124
## x76 0.005768847558 -0.00399831536 -0.00242341946 0.00781138882
## x77 0.000057143098 -0.00041514568 0.00480067060 -0.00237253174
## x79 0.001402176908 0.00404270193 0.00761349375 -0.00590974635
## x80 -0.000051922469 0.00007816811 -0.00238691919 0.00370404457
## x81 0.002504110304 -0.01138175725 0.00089500525 -0.01042509151
## x82 0.009425483573 -0.00756202509 -0.00630038383 -0.01137233139
## x83 0.000439173578 0.00863183873 -0.00108731360 -0.00598667467
## x84 0.006653784664 -0.00125831448 0.00353351584 0.00483130495
## x85 0.000022086456 0.00058952497 0.00917329187 -0.00549977297
## x86 -0.010548907004 0.00699496194 0.00190066297 0.01695403865
## x87 -0.005655439509 -0.00482343136 0.00085138267 0.00155377361
## x88 0.006325839837 -0.00815768421 -0.00301838858 -0.01031403442
## x89 0.003547063301 -0.00248926848 0.00314082862 -0.00870917504
## x90 0.009585710267 -0.00248239481 -0.00156110858 -0.00334986223
## x92 0.006811346062 0.00762042544 -0.00082579627 0.01382444638
## x93 -0.004973999945 -0.01159582199 -0.00180522610 -0.00267282920
## x94 -0.005484287328 -0.00943136734 -0.01145252320 0.00333473197
## x95 0.005067955568 -0.00402464465 -0.01069671908 -0.00511968512
## x96 0.005066854393 0.00200355150 0.00231425106 0.00101074598
## x97 -0.001247244506 -0.00128674537 0.01062801188 0.00655859018
## x98 0.004878268464 0.00099216615 -0.00208354998 -0.00332476158
## x99 0.004995720038 0.00083601261 -0.00904225215 0.00181703227
## x101 0.002807668687 0.00058729505 0.01581907425 -0.00115188077
## x102 -0.003714715059 0.00192900652 0.00278332343 0.00649170451
## x103 0.003699625388 -0.00585335083 0.00687168756 0.00545738126
## x104 -0.001201080726 0.00145158579 0.00285635519 0.01011802873
## x105 0.001730468860 -0.00511673657 -0.00009442238 0.00623340299
## x106 -0.008638823784 -0.00251378112 0.00388709211 -0.00226517678
## target 0.004259163778 -0.00089520238 -0.00473278720 0.02286670227
## x12 x13 x14 x15
## x1 0.00173343403 -0.00484290581 -0.00315925567 0.008702971710
## x3 0.00335712242 0.00291910479 0.00291479485 -0.002535744626
## x4 0.00124322832 0.00185808594 -0.00060999214 0.006560574426
## x6 0.00356007074 0.01003167317 0.00164728295 -0.003851560045
## x7 -0.00489579933 -0.00310209992 0.00110784516 -0.000994608068
## x8 -0.00997582549 -0.00157446373 -0.01068025595 0.001812883134
## x9 0.00574413657 0.00561597990 0.00709476205 -0.003190625194
## x10 0.00113574213 -0.00555813633 0.00207600083 0.002907879466
## x11 0.00701796252 0.00820356275 0.01611755957 0.001101932046
## x12 1.00000000000 -0.00278317973 -0.00202213727 0.004250425476
## x13 -0.00278317973 1.00000000000 -0.00598272551 0.002327091548
## x14 -0.00202213727 -0.00598272551 1.00000000000 -0.008747308910
## x15 0.00425042548 0.00232709155 -0.00874730891 1.000000000000
## x16 -0.01739416568 0.01001977005 -0.00137521128 -0.005983703524
## x17 0.00274060911 0.01211698636 -0.00661942629 -0.000918361879
## x18 0.00273376950 -0.00376024238 -0.00422857312 0.005951875141
## x19 -0.00184966306 -0.00555855502 0.00345984417 0.002104336100
## x20 -0.00677783600 -0.00226398483 -0.00292495581 0.000285428242
## x21 0.00912481850 -0.00459605084 0.00203677191 -0.003586380949
## x22 -0.00191580093 -0.00008053166 0.00016023451 0.010263065729
## x23 -0.00302744663 0.00738337438 -0.01145428986 0.004943663636
## x24 0.00810816108 -0.00313155677 -0.00603651806 0.003498507796
## x25 0.00256160115 -0.00147789050 -0.01279245133 -0.012667678209
## x26 -0.00552452625 0.00810038930 -0.00229355386 0.007256327204
## x29 0.00903413680 -0.00325357775 -0.00660361321 0.002207483281
## x30 -0.00321553113 -0.00503540591 -0.01111779876 0.001453174519
## x31 0.00551366730 0.00308689349 0.00044867949 0.007195555579
## x32 -0.00366259455 0.01802985026 -0.00325667818 -0.000638742117
## x33 0.00265638603 -0.01199189893 0.00574019179 0.003390582541
## x34 -0.00393275234 -0.00953778523 0.00534132459 0.004670836741
## x35 -0.00782406687 0.00490880043 0.00552112255 0.004714129423
## x36 -0.00566002908 0.00563749085 -0.00128851746 0.005191027849
## x37 -0.00351837744 0.00390936897 0.01048589803 0.010324092452
## x38 -0.00779005674 -0.00144442930 -0.00571198956 -0.010410594533
## x39 -0.00491799922 0.00662632323 0.00369741331 0.000000123538
## x40 0.00523510971 -0.01101457903 -0.00098421635 0.000660610408
## x41 -0.00875807127 0.00198561897 -0.00352177606 0.009277551407
## x42 -0.00222543030 0.01265753846 0.00171624624 0.003687111363
## x43 0.00172212973 0.00652311814 -0.00390859236 -0.001635819484
## x44 0.01134100772 0.00607808517 0.00040428538 0.004142613131
## x45 -0.00181595849 -0.00903454197 0.00746630224 -0.005305380946
## x46 -0.00652544892 0.00303857527 -0.01085590688 0.000689912158
## x47 -0.00282174310 -0.00742645899 0.00815930260 0.001297004845
## x48 -0.00480376072 -0.01049740283 -0.00986189426 -0.011080880285
## x49 -0.00703574575 0.00342301027 0.00554867347 0.008662026474
## x50 0.00404934771 -0.00788729475 -0.00260211289 0.005814731741
## x51 -0.00253237924 0.00076829648 -0.00206618014 -0.001263224075
## x52 -0.00117078955 0.00281774127 -0.00681027512 0.003765584837
## x54 -0.00259140191 -0.01165685821 0.00099115601 -0.004927726501
## x55 0.00522333514 0.00185355894 0.01726882936 -0.002261679432
## x56 0.00233932322 0.00590460432 -0.00340278568 0.002839548465
## x57 0.00608743516 -0.01231360058 0.00665551693 0.006345252942
## x58 -0.01220543424 -0.00132577761 0.00583254412 0.003912647044
## x60 0.00303955645 0.01041689620 0.00183125313 -0.003674778530
## x61 0.00655331548 -0.00675139361 0.00100597215 0.005210862684
## x63 0.00605573291 -0.01239631140 0.00678222065 0.006502448600
## x64 0.00902323311 -0.00292708688 -0.00656895774 0.002255930396
## x65 -0.00384885464 -0.00438139729 0.00092949859 -0.009480586447
## x66 -0.00896882518 -0.00315202393 -0.00681902404 0.009032194050
## x68 -0.00281383222 -0.01037594795 0.00602246857 -0.002472441375
## x69 -0.01476868317 -0.00523679085 0.01065638952 -0.000557662124
## x70 -0.01900984111 -0.00943060954 -0.00308311434 0.010749758628
## x71 -0.00399045812 0.00689172884 -0.00631014479 -0.003684818154
## x72 0.00616544034 0.00169984059 0.00800765914 -0.007659133523
## x73 0.00529692400 -0.00040658695 -0.00118249097 -0.003081079351
## x74 0.00195774798 -0.00520809340 -0.00007245535 -0.011429570658
## x75 -0.00412616278 -0.00432361410 -0.00464059215 0.007649199187
## x76 0.00304121130 0.01041346326 0.00183008073 -0.003672762756
## x77 -0.00542914427 -0.01027050969 0.00554171368 0.003812556466
## x79 0.00145041636 -0.00258595917 -0.00462782863 0.010384889837
## x80 -0.00104351101 -0.00670335170 -0.00412480389 0.002660742333
## x81 0.00638418398 -0.00715441076 -0.00165613724 0.003250666254
## x82 0.00508571926 -0.01631469054 0.00573777528 -0.003989567591
## x83 0.00207218428 -0.00165416904 -0.00993980638 0.003211138437
## x84 0.00551364182 0.00308695803 0.00044877398 0.007195427519
## x85 -0.00897066453 -0.00315193827 -0.00681836460 0.009032123225
## x86 -0.00014418637 -0.00745111224 0.97545766052 -0.007649585445
## x87 0.00461671093 -0.00894376532 -0.00135205379 -0.004515347223
## x88 -0.00366697447 0.01803772343 -0.00325962948 -0.000630702046
## x89 -0.00271471003 0.00289169866 0.00574928062 0.003046486044
## x90 0.00390899032 -0.00853386638 -0.00187285765 0.005246009188
## x92 -0.00154864317 -0.00025690679 -0.00008627035 0.010289864743
## x93 0.00172743042 0.01016061939 -0.01249476728 0.005552837941
## x94 -0.00561263055 -0.00258902431 -0.00343299960 -0.000583326175
## x95 -0.00286028543 -0.00078408672 -0.00463494484 0.003830670582
## x96 0.00521907609 -0.01166976043 0.00585779005 0.005761724096
## x97 -0.00129003055 -0.00101418481 0.00707094318 0.010638767728
## x98 -0.00144106550 -0.00264138420 -0.01139515974 -0.006857978484
## x99 0.00022811270 -0.00451494186 -0.00509899974 -0.006623641125
## x101 -0.00677751781 -0.00226838870 -0.00291378800 0.000279764225
## x102 0.00712667023 0.00305827815 -0.00771781583 -0.006805987315
## x103 0.00008436634 0.01686185583 0.00276955478 0.004942953551
## x104 -0.00486341629 -0.00989126855 0.00679507755 0.005924254366
## x105 0.00214848911 -0.00228853719 -0.00291321011 0.004881940691
## x106 -0.00802170113 -0.00089645880 0.00485228704 -0.001710708736
## target 0.00502717375 -0.06715429390 0.00790445806 -0.023381810753
## x16 x17 x18 x19 x20
## x1 -0.0026129316 0.0064194441 0.0028937059 0.0028082615 0.005728961189
## x3 -0.0008546989 0.0014975668 0.0044855555 -0.0019550481 0.002593749927
## x4 -0.0084681219 0.0188269615 0.0056016280 -0.0011535133 0.001124931250
## x6 0.0102763446 -0.0040838052 -0.0034844123 -0.0010480585 -0.006666356933
## x7 -0.0066364170 -0.0031591711 0.0071568133 0.0018822566 -0.001737479025
## x8 -0.0105260891 -0.0032073880 0.0018874641 0.0030721819 0.002812180513
## x9 -0.0029675392 0.0015325804 -0.0056969629 0.0032469314 0.000586596978
## x10 0.0035185597 0.0019440717 -0.0001798432 0.0104879367 0.015816630284
## x11 0.0007587228 -0.0053340740 0.0045203368 0.0010695415 -0.001156264766
## x12 -0.0173941657 0.0027406091 0.0027337695 -0.0018496631 -0.006777836004
## x13 0.0100197700 0.0121169864 -0.0037602424 -0.0055585550 -0.002263984827
## x14 -0.0013752113 -0.0066194263 -0.0042285731 0.0034598442 -0.002924955806
## x15 -0.0059837035 -0.0009183619 0.0059518751 0.0021043361 0.000285428242
## x16 1.0000000000 0.0057126785 0.0017042357 0.0073364400 0.003998153924
## x17 0.0057126785 1.0000000000 0.0083521334 -0.0073910573 0.002583311576
## x18 0.0017042357 0.0083521334 1.0000000000 0.0020281147 -0.005486560534
## x19 0.0073364400 -0.0073910573 0.0020281147 1.0000000000 0.004199205682
## x20 0.0039981539 0.0025833116 -0.0054865605 0.0041992057 1.000000000000
## x21 -0.0030256481 -0.0037368604 -0.0010342814 -0.0081165313 0.001606259347
## x22 0.0033740558 0.0060093430 -0.0118438760 -0.0034879904 -0.004733435108
## x23 -0.0021553170 0.0058070434 0.0067595893 0.0014151308 -0.005958247450
## x24 -0.0025132182 0.0036524792 -0.0007753581 -0.0094158218 0.007472472223
## x25 -0.0043229280 -0.0014144603 -0.0018067465 0.0066216276 -0.004592589082
## x26 -0.0045332328 -0.0048487618 0.0035917172 -0.0048615061 0.001174650834
## x29 -0.0031317956 0.0039251005 -0.0026162325 -0.0094617924 0.005433527804
## x30 -0.0086602637 0.0077712953 -0.0017007177 -0.0021462001 0.003535881010
## x31 0.0011062544 0.0003478050 -0.0070272624 -0.0061857909 0.004352499727
## x32 -0.0012726105 -0.0003126364 -0.0124614356 -0.0072942287 -0.001744312553
## x33 -0.0070318853 0.0114933076 0.0055048143 0.0149905585 0.005250992620
## x34 0.0039092138 -0.0014731805 0.0073717893 0.0005276017 -0.000941717186
## x35 0.0142183700 -0.0170012452 0.0062138329 -0.0044468116 -0.003867654170
## x36 0.0024309080 0.0100459198 0.0006926434 -0.0071994308 -0.000339715752
## x37 0.0004700045 -0.0022177792 0.0051846576 0.0092885677 -0.005464802089
## x38 0.0029991780 -0.0044254414 -0.0174714130 0.0045074920 0.009187081214
## x39 0.0036877842 0.0129157422 -0.0104911196 0.0132717056 0.002531157176
## x40 0.0034516272 -0.0061604673 -0.0020362042 0.0019006724 0.003090388653
## x41 0.0014720073 0.0084626401 0.0011799840 0.0051679231 0.006758721271
## x42 0.0029488369 -0.0005247365 -0.0028138693 -0.0031083285 0.009469093448
## x43 0.0042106767 -0.0007572116 -0.0138075669 -0.0089372034 0.009349578741
## x44 0.0079144222 -0.0002658833 -0.0011101874 0.0002433346 0.005044899332
## x45 -0.0012286287 0.0029457715 -0.0002073913 -0.0059196930 0.006509679118
## x46 0.0006042379 0.0006407294 -0.0054768699 -0.0029698587 -0.002641820620
## x47 -0.0084922412 0.0023303755 -0.0110006821 0.0015967952 -0.004158699817
## x48 0.0041788566 -0.0041202179 -0.0013087108 -0.0010175081 0.001069440056
## x49 0.0046625963 -0.0097767282 -0.0045266626 -0.0042623269 0.004419830265
## x50 -0.0009924687 0.0032035153 0.0016405970 0.0001544944 0.007769913238
## x51 -0.0022931157 -0.0042193290 0.0063988378 0.0034949008 -0.010034151963
## x52 -0.0063957059 0.0007111457 0.0020111648 0.0027225700 0.002277114498
## x54 -0.0107590933 0.0050660818 -0.0015165621 -0.0029897808 0.015895302598
## x55 -0.0101390816 0.0003546956 -0.0028372461 0.0077764689 0.012057721813
## x56 -0.0058963431 -0.0045381477 0.0088211426 -0.0074666627 0.004190495582
## x57 0.0038273257 0.0016267308 -0.0048421000 0.0107905522 -0.001894367050
## x58 -0.0092778247 -0.0095027104 0.0019031430 0.0066710278 0.008370041344
## x60 0.0097056617 -0.0042115856 -0.0040433301 -0.0007799993 -0.006819975855
## x61 -0.0003867860 0.0006472844 0.0004088480 0.0017406407 0.004486531516
## x63 0.0037408315 0.0014762331 -0.0049022633 0.0107561459 -0.001884337287
## x64 -0.0030006472 0.0039654904 -0.0024379997 -0.0096516699 0.005684284139
## x65 -0.0048840944 0.0120579236 -0.0051343060 0.0014238225 0.000006865111
## x66 -0.0013639257 -0.0018987935 0.0116822057 -0.0040438978 0.003243668449
## x68 -0.0004076806 -0.0043545727 0.0045590755 0.0029620099 0.006854881233
## x69 -0.0045108723 -0.0111443975 -0.0055290191 -0.0041690110 0.003231307120
## x70 0.0008943081 -0.0058965621 0.0051664183 0.0069135126 0.005528408992
## x71 -0.0040641257 -0.0007765071 0.0135218590 -0.0021603550 0.000105038521
## x72 0.0027130732 -0.0001310506 0.0056380057 0.0097579988 -0.014649142765
## x73 -0.0016241540 0.0066553650 0.0055683600 -0.0103714840 0.005865445750
## x74 0.0055904108 0.0122350941 -0.0099645502 -0.0064344425 0.007082768580
## x75 -0.0020267227 -0.0068409508 0.0104857950 0.0037876972 0.115248291864
## x76 0.0097075558 -0.0042123108 -0.0040410196 -0.0007814087 -0.006820530801
## x77 0.0076110099 0.0010994422 -0.0050411942 -0.0017052375 0.000225148473
## x79 0.0102534452 0.0039798942 0.0073769638 -0.0036966633 0.001245739167
## x80 0.0008597872 0.0004950050 -0.0073320596 -0.0057541814 -0.002414657775
## x81 -0.0079173791 0.0088033213 -0.0065657756 0.0051541208 -0.002249299661
## x82 0.0050105584 -0.0001900893 0.0018167358 -0.0062993605 -0.001431421624
## x83 -0.0074840414 -0.0085956057 0.0041580712 -0.0040215592 0.002425033404
## x84 0.0011062591 0.0003477965 -0.0070272850 -0.0061857744 0.004352583273
## x85 -0.0013626170 -0.0018971037 0.0116832904 -0.0040446512 0.003242723859
## x86 0.0001697424 -0.0060427724 -0.0033531522 0.0014129659 -0.001311866266
## x87 0.0021699141 0.0017763781 0.0032302322 0.0037315441 -0.007196059647
## x88 -0.0012773945 -0.0003161830 -0.0124585686 -0.0072986776 -0.001745859921
## x89 0.0082214534 -0.0015427869 0.0102081814 -0.0032021025 0.000003180418
## x90 -0.0011633258 0.0029005706 0.0015919383 0.0003604256 0.007241322045
## x92 0.0033841209 0.0062690567 -0.0117490951 -0.0034411939 -0.004817384381
## x93 -0.0065568139 -0.0049176965 -0.0000680892 -0.0018451017 0.007539874404
## x94 0.0067168623 0.0001539524 -0.0031578495 0.0050308023 0.003111284655
## x95 -0.0028437292 0.0036549729 0.0012610978 0.0011999236 -0.008728923538
## x96 0.0030492279 0.0004724014 -0.0029908389 0.0113822895 -0.004496244563
## x97 -0.0007369735 -0.0037501255 0.0064696691 0.0056554670 0.007498221129
## x98 0.0126809095 0.0014178518 -0.0053202560 -0.0105525245 0.002062355395
## x99 0.0025968122 0.0085037645 -0.0013423481 -0.0028003802 0.001244069116
## x101 0.0039986290 0.0025787588 -0.0054679966 0.0042273779 0.999998798033
## x102 -0.0041749905 -0.0007741654 -0.0146862741 0.0050369477 -0.004234969527
## x103 0.0074191659 0.0074360803 -0.0095430796 -0.0008410043 -0.002985366947
## x104 0.0036913285 0.0011972155 0.0005874184 0.0050747160 -0.004288756274
## x105 0.0016563614 0.0088459380 0.9800415672 0.0007172076 -0.005506263240
## x106 -0.0017931619 0.0043770298 0.0089137705 -0.0003108337 -0.001326903641
## target 0.0146423138 -0.0044565638 0.1452504090 0.0122453501 -0.215884678986
## x21 x22 x23 x24
## x1 0.00474230919 -0.00588270596 -0.00618961361 -0.0002203695
## x3 0.01239413599 0.00612078195 -0.00005792338 0.0048442317
## x4 -0.00391290290 -0.00761404787 0.00458324444 0.0112850686
## x6 0.00131346254 -0.00401684403 -0.00562415551 -0.0090347534
## x7 0.00071694922 0.00413445058 -0.00586981201 -0.0019424113
## x8 0.01146913068 0.00681375243 -0.00867553262 -0.0083400423
## x9 0.01001349752 0.00762359842 0.00002387407 -0.0019344325
## x10 0.00247241305 -0.00076260348 0.00708747347 -0.0001155283
## x11 -0.00584586132 0.01384420948 -0.01033570614 0.0109985642
## x12 0.00912481850 -0.00191580093 -0.00302744663 0.0081081611
## x13 -0.00459605084 -0.00008053166 0.00738337438 -0.0031315568
## x14 0.00203677191 0.00016023451 -0.01145428986 -0.0060365181
## x15 -0.00358638095 0.01026306573 0.00494366364 0.0034985078
## x16 -0.00302564812 0.00337405584 -0.00215531703 -0.0025132182
## x17 -0.00373686042 0.00600934303 0.00580704343 0.0036524792
## x18 -0.00103428136 -0.01184387598 0.00675958927 -0.0007753581
## x19 -0.00811653130 -0.00348799038 0.00141513085 -0.0094158218
## x20 0.00160625935 -0.00473343511 -0.00595824745 0.0074724722
## x21 1.00000000000 0.01453642176 -0.00106034755 0.0064195370
## x22 0.01453642176 1.00000000000 0.00558077501 0.0006209074
## x23 -0.00106034755 0.00558077501 1.00000000000 -0.0046089200
## x24 0.00641953704 0.00062090742 -0.00460892004 1.0000000000
## x25 -0.01273137324 -0.00699616559 -0.00159271854 0.0048942982
## x26 0.00094252780 0.00208222160 -0.00551356832 0.0010087992
## x29 0.00614286156 -0.00007254303 -0.00395971330 0.9930851942
## x30 -0.00205266241 0.00387852063 0.00194989433 0.0007010985
## x31 -0.01443989565 0.00242077241 -0.00579871353 0.0086579185
## x32 -0.00028999981 0.00527832653 -0.00545848501 -0.0071486576
## x33 0.00314728291 0.00031836724 0.00458184773 0.0021708897
## x34 -0.00249287351 -0.00942088765 0.00063160169 0.0006494693
## x35 0.00163593902 0.00454854416 -0.00628098842 0.0016370020
## x36 -0.00204044190 -0.00105603078 0.00011627957 0.0001180926
## x37 -0.00003981204 0.00414896879 -0.00941376522 -0.0045972581
## x38 -0.00575447736 0.01050391128 -0.00209797510 0.0073860855
## x39 0.00036389743 0.00476837229 0.00530828809 -0.0102362636
## x40 0.00158243045 -0.01025294092 -0.00322747043 -0.0002373051
## x41 -0.00949770251 -0.00363454066 0.00031307507 0.0126689503
## x42 0.00215562095 0.00180488684 -0.00820514483 -0.0024335909
## x43 -0.00612596629 0.00397298317 -0.00508557865 0.0015997895
## x44 0.00224853989 0.00282112520 -0.00795543128 0.0174142687
## x45 0.00616509587 0.00419348118 -0.00381121856 -0.0057322098
## x46 0.00004695759 -0.00737804965 -0.00119026346 -0.0022608604
## x47 0.00084285881 0.00755189931 0.00141186431 0.0174953548
## x48 0.00724541648 0.00134890498 -0.00755417726 0.0016853136
## x49 0.00202653387 0.00520810055 0.00286879389 0.0065802728
## x50 -0.00906070016 -0.00635765329 -0.00123752538 -0.0023811518
## x51 -0.01435779299 0.00015688919 0.00167031834 -0.0055314500
## x52 0.01094279231 -0.00058022731 0.00141122610 0.0042985435
## x54 0.00710936414 -0.00158267275 0.00092724259 -0.0042535053
## x55 0.00376964439 -0.00980121986 0.00445395281 0.0015763522
## x56 -0.00138687647 -0.00302503110 -0.00055417683 -0.0022025392
## x57 0.00373588836 -0.00092592684 -0.00625050120 0.0028588976
## x58 0.00784316726 -0.00500051970 -0.01135028013 -0.0072142317
## x60 0.00205010876 -0.00383710117 -0.00484182386 -0.0099479941
## x61 0.00302219507 -0.00864931464 0.00663317209 -0.0055160467
## x63 0.00370922212 -0.00097592873 -0.00628808524 0.0030559895
## x64 0.00587337395 0.00021754632 -0.00398303368 0.9936159834
## x65 0.00156169492 0.00455479422 -0.00823544020 0.0049885490
## x66 0.00926551035 -0.00053529272 -0.00699278825 0.0051774762
## x68 0.00176398384 0.00946298218 0.00513028682 -0.0016043959
## x69 0.00323416457 0.00783078577 0.00091584463 0.0073895038
## x70 -0.00124449343 -0.00028880059 0.00439799338 -0.0030334760
## x71 0.01394261953 0.00595525619 0.00122018278 -0.0119037526
## x72 -0.00379791352 -0.00095757771 -0.00611991707 0.0018129102
## x73 0.00193803063 -0.00136602872 -0.00220774189 -0.0066589853
## x74 0.01573727519 0.00022795502 0.00564979939 0.0110731620
## x75 -0.01258460380 0.00597101367 0.00322380305 0.0159573034
## x76 0.00205056137 -0.00383645559 -0.00484009577 -0.0099503358
## x77 -0.00566249224 0.00319623225 -0.00067764911 -0.0058338254
## x79 -0.00492144121 0.00324572138 -0.00291093506 -0.0088736690
## x80 0.00994004752 0.00439191632 0.00625542373 0.0037762662
## x81 0.00209465922 -0.00553759851 -0.01392731099 -0.0033975046
## x82 0.00806964682 -0.00879022669 0.00431618734 -0.0061435728
## x83 -0.00750369431 0.00686237553 0.00526493474 0.0078689267
## x84 -0.01444003380 0.00242079530 -0.00579880990 0.0086580116
## x85 0.00926631089 -0.00053400649 -0.00699248406 0.0051775965
## x86 0.00230707844 0.00084562863 -0.00922456257 -0.0036631712
## x87 0.00503618777 -0.00018773224 0.01855498978 -0.0012654210
## x88 -0.00028791214 0.00528061539 -0.00546427193 -0.0071482211
## x89 -0.00591234520 -0.00989933071 0.00152825941 0.0020748541
## x90 -0.00916602803 -0.00642709697 -0.00087966361 -0.0026591504
## x92 0.01475599194 0.99963861574 0.00547083849 0.0004241505
## x93 0.00304345196 0.00402216510 -0.00107715909 0.0027387915
## x94 -0.00437272321 -0.00334997976 -0.00292349401 -0.0039031482
## x95 -0.00622777919 0.00494543985 -0.00502169282 0.0048973556
## x96 -0.00023498927 -0.00083289944 -0.00558912757 0.0012769754
## x97 -0.00554149781 -0.01278304838 -0.00127065233 -0.0070928217
## x98 -0.00852181405 -0.00072809076 0.00568105913 -0.0016322516
## x99 0.00047710696 0.00766233465 -0.00511268570 0.0032757419
## x101 0.00162619054 -0.00473764814 -0.00594971455 0.0074580742
## x102 0.00264170413 -0.01160681674 -0.01374143474 -0.0102708516
## x103 0.00564766229 0.00520014352 -0.00091407075 -0.0088618473
## x104 0.00178360038 0.01217573244 0.00485808198 -0.0035209492
## x105 0.00112232705 -0.01078186241 0.00647480584 -0.0034350216
## x106 0.00117637608 -0.01531089164 0.00882155457 -0.0101342410
## target -0.01257516127 0.01167759203 -0.00698845252 -0.0330379323
## x25 x26 x29 x30 x31
## x1 -0.00360677835 0.00125185894 0.00050665899 0.0030276575 -0.0105299159
## x3 0.00752843096 -0.00585656119 0.00476336894 0.0115602799 0.0031676450
## x4 0.00166971366 0.00899493339 0.01254974589 0.0033141957 -0.0042704016
## x6 -0.00066500951 -0.00120782964 -0.00987849209 -0.0084951775 -0.0058738045
## x7 0.00434117412 0.00322707329 -0.00111220787 -0.0006882836 -0.0019897275
## x8 0.00273828446 -0.00404756183 -0.00871940398 -0.0050290387 0.0066538336
## x9 0.01132818661 -0.00022638547 -0.00212831987 -0.0001524610 -0.0012583673
## x10 0.00456614710 -0.00366023293 -0.00066434159 0.0040626760 0.0035336385
## x11 0.00319965639 -0.00342579595 0.01035857076 0.0020817240 0.0048311935
## x12 0.00256160115 -0.00552452625 0.00903413680 -0.0032155311 0.0055136673
## x13 -0.00147789050 0.00810038930 -0.00325357775 -0.0050354059 0.0030868935
## x14 -0.01279245133 -0.00229355386 -0.00660361321 -0.0111177988 0.0004486795
## x15 -0.01266767821 0.00725632720 0.00220748328 0.0014531745 0.0071955556
## x16 -0.00432292796 -0.00453323278 -0.00313179558 -0.0086602637 0.0011062544
## x17 -0.00141446026 -0.00484876181 0.00392510046 0.0077712953 0.0003478050
## x18 -0.00180674646 0.00359171721 -0.00261623247 -0.0017007177 -0.0070272624
## x19 0.00662162760 -0.00486150611 -0.00946179245 -0.0021462001 -0.0061857909
## x20 -0.00459258908 0.00117465083 0.00543352780 0.0035358810 0.0043524997
## x21 -0.01273137324 0.00094252780 0.00614286156 -0.0020526624 -0.0144398957
## x22 -0.00699616559 0.00208222160 -0.00007254303 0.0038785206 0.0024207724
## x23 -0.00159271854 -0.00551356832 -0.00395971330 0.0019498943 -0.0057987135
## x24 0.00489429818 0.00100879925 0.99308519423 0.0007010985 0.0086579185
## x25 1.00000000000 -0.00666040033 0.00431341264 0.0009792545 0.0005456909
## x26 -0.00666040033 1.00000000000 0.00115802839 0.0032831160 0.0056120215
## x29 0.00431341264 0.00115802839 1.00000000000 0.0001880760 0.0081139930
## x30 0.00097925446 0.00328311603 0.00018807597 1.0000000000 0.0002832293
## x31 0.00054569092 0.00561202153 0.00811399304 0.0002832293 1.0000000000
## x32 -0.00811610413 0.00503886005 -0.00744809427 0.0031567665 -0.0077431816
## x33 -0.00740355675 0.00484163212 0.00230396597 -0.0006761303 -0.0037058566
## x34 -0.00036822630 0.00170026225 0.00082964571 0.0048200681 -0.0041705330
## x35 -0.01708001715 0.00890806632 0.00145799209 0.0083819597 -0.0035709223
## x36 -0.00787344972 0.00101681454 -0.00071816467 -0.0099284631 -0.0055125970
## x37 -0.00964745449 0.00120090741 -0.00414198081 -0.0030165509 0.0056313107
## x38 0.00668005386 -0.00267035785 0.00747959503 -0.0066737708 -0.0096127178
## x39 0.00079120303 0.00069861114 -0.00973103748 -0.0115190194 -0.0060190679
## x40 -0.00620776659 -0.00356635443 -0.00014772269 -0.0112407652 -0.0015739512
## x41 -0.00396870244 -0.00427418147 0.01367227890 -0.0043109202 0.0091772900
## x42 -0.00704187341 -0.00952940619 -0.00250620603 -0.0130595590 0.0053189232
## x43 0.00527439922 0.01159951617 0.00018272248 0.0071415134 0.6287787260
## x44 -0.00714709394 0.00409444418 0.01677375174 -0.0006537704 0.0055687168
## x45 0.00651260481 0.00051264397 -0.00568075858 -0.0023742871 0.0028086836
## x46 0.00149878043 -0.00142788435 -0.00132907914 0.0051834460 0.0061653723
## x47 0.00131214229 -0.00684281271 0.01677132198 0.0008043336 -0.0007784414
## x48 -0.00358571845 -0.00283887266 0.00177880347 0.0007008580 0.0011963099
## x49 0.00739927857 -0.00948517427 0.00678472505 0.0098039499 -0.0023350800
## x50 -0.00379853626 0.01075859549 -0.00242483529 -0.0105203848 -0.0035628256
## x51 -0.00085587233 -0.00054132161 -0.00588466438 0.0100313386 0.0045154614
## x52 -0.00543102997 0.00145483645 0.00445360605 -0.0082535109 0.0041721026
## x54 -0.00268096850 -0.00101758017 -0.00434445384 0.0029063942 0.0026598510
## x55 -0.00198692672 0.00451264986 0.00210661991 0.0069440825 -0.0083457519
## x56 -0.01288727423 0.01659190150 -0.00191508650 -0.0066083534 -0.0195056029
## x57 0.00407937398 0.00551052820 0.00183628381 0.0027307905 -0.0102259945
## x58 -0.00178630132 -0.00057477982 -0.00688369055 0.0064752183 -0.0020464642
## x60 -0.00136259758 -0.00145187793 -0.01078048430 -0.0088912422 -0.0063567221
## x61 0.00502941277 0.00070536827 -0.00688519715 -0.0164481055 -0.0023229044
## x63 0.00394503803 0.00553297895 0.00202826201 0.0027580608 -0.0101819820
## x64 0.00452801775 0.00101235451 0.99944952012 0.0001535818 0.0083820773
## x65 0.00062425698 -0.00309852892 0.00548389861 -0.0030441247 -0.0018729318
## x66 -0.00628501564 0.00457163796 0.00401693765 0.0076480339 -0.0077704598
## x68 0.00004342874 0.00240988216 -0.00226693282 0.0008784100 -0.0009843311
## x69 0.00647095610 0.00466076790 0.00806520134 0.0089284905 0.0097365708
## x70 0.01658597137 0.00274712958 -0.00254929490 -0.0018223110 -0.0047589295
## x71 0.00807738761 0.00025721824 -0.01124249604 -0.0015697727 -0.0040615067
## x72 0.01061172917 -0.00141454551 0.00214926749 -0.0066378402 0.0103561511
## x73 0.00111373636 -0.00703527203 -0.00525620718 -0.0016618977 0.0089657773
## x74 -0.00436416250 0.00718838035 0.01113547779 -0.0045787785 -0.0114415462
## x75 -0.00232723864 -0.00327925460 0.01647229885 -0.0038604186 0.0084116107
## x76 -0.00136284752 -0.00144921802 -0.01078274969 -0.0088922666 -0.0063573565
## x77 0.00720672585 -0.00941945572 -0.00572344797 0.0004421237 0.0071127253
## x79 0.00180437564 0.01580437245 -0.00868948321 -0.0072770802 -0.0002598015
## x80 -0.00630117926 0.00868509097 0.00269502008 0.0047318263 0.0045386873
## x81 0.01156625155 0.01440451327 -0.00281426113 -0.0042868946 0.0135203475
## x82 0.00978451670 -0.00006336198 -0.00678624754 0.0039288730 -0.0007452406
## x83 -0.00599802548 0.00361172925 0.00916964708 0.0049496520 -0.0030904222
## x84 0.00054571488 0.00561202410 0.00811408919 0.0002832284 0.9999999999
## x85 -0.00628537447 0.00457155558 0.00401705153 0.0076469154 -0.0077703603
## x86 -0.00967340516 -0.00191270067 -0.00401682050 -0.0120223167 -0.0003331667
## x87 -0.00049878318 0.00538501538 -0.00065390636 0.0028319473 -0.0028831191
## x88 -0.00812176781 0.00595991808 -0.00744739415 0.0031599239 -0.0077370244
## x89 -0.00170765541 0.00186311097 0.00296710322 -0.0076681602 0.0063602491
## x90 -0.00376955330 0.01091828576 -0.00272578191 -0.0103145367 -0.0037115742
## x92 -0.00683657426 0.00191705406 -0.00025074572 0.0036332055 0.0019159594
## x93 -0.00089861009 0.00876299920 0.00419001028 -0.0005532602 -0.0027275895
## x94 -0.00038879716 -0.00289040084 -0.00432123099 -0.0023570691 0.0011038414
## x95 0.00169567727 0.00973988617 0.00468765418 -0.0023654983 -0.0020867122
## x96 0.00370618600 0.00514761580 0.00019846780 0.0052790962 -0.0086786589
## x97 -0.00166361336 -0.00844184499 -0.00564219152 0.0097503843 -0.0090897006
## x98 -0.00268089319 0.00478162216 -0.00243142760 -0.0002489277 -0.0058421623
## x99 0.01022845351 -0.01003753601 0.00360684321 -0.0126997885 -0.0127325584
## x101 -0.00460178567 0.00116364597 0.00541959196 0.0035373697 0.0031844322
## x102 0.00109725858 0.01053451834 -0.01001895085 -0.0068388931 -0.0019116434
## x103 -0.00065124250 0.00497296460 -0.00908589174 -0.0053662187 0.0032204288
## x104 0.01214011225 0.00090779687 -0.00350189928 -0.0102575030 0.0046747434
## x105 -0.00223673004 0.00428601302 -0.00500104820 -0.0022158490 -0.0059709949
## x106 0.00466985413 0.00170301773 -0.01091286827 -0.0068177131 0.0019692438
## target -0.07384704039 0.00753397024 -0.03288783610 -0.0049996440 -0.0216696208
## x32 x33 x34 x35
## x1 -0.00170189571 0.001559492854 -0.00432719555 0.00308614245
## x3 -0.01432675762 -0.001929160989 -0.00438263283 -0.00731974888
## x4 0.00687147612 0.004851185959 -0.00369881624 0.00642468350
## x6 -0.00258206573 -0.007628624029 0.00102668094 0.00618238693
## x7 -0.01200713659 0.010875615433 -0.00878713351 0.00377998667
## x8 0.00633046147 -0.015709310093 0.00101628483 0.00005789121
## x9 -0.00815715849 0.002140952328 -0.00563710445 -0.00040516795
## x10 -0.00301462122 0.006786534427 0.00035578541 0.00225957394
## x11 -0.01031133648 0.007257412562 0.00789043211 0.00212935955
## x12 -0.00366259455 0.002656386029 -0.00393275234 -0.00782406687
## x13 0.01802985026 -0.011991898925 -0.00953778523 0.00490880043
## x14 -0.00325667818 0.005740191789 0.00534132459 0.00552112255
## x15 -0.00063874212 0.003390582541 0.00467083674 0.00471412942
## x16 -0.00127261050 -0.007031885291 0.00390921376 0.01421836997
## x17 -0.00031263637 0.011493307600 -0.00147318053 -0.01700124520
## x18 -0.01246143556 0.005504814316 0.00737178926 0.00621383286
## x19 -0.00729422868 0.014990558472 0.00052760174 -0.00444681160
## x20 -0.00174431255 0.005250992620 -0.00094171719 -0.00386765417
## x21 -0.00028999981 0.003147282909 -0.00249287351 0.00163593902
## x22 0.00527832653 0.000318367239 -0.00942088765 0.00454854416
## x23 -0.00545848501 0.004581847729 0.00063160169 -0.00628098842
## x24 -0.00714865755 0.002170889676 0.00064946927 0.00163700200
## x25 -0.00811610413 -0.007403556753 -0.00036822630 -0.01708001715
## x26 0.00503886005 0.004841632121 0.00170026225 0.00890806632
## x29 -0.00744809427 0.002303965970 0.00082964571 0.00145799209
## x30 0.00315676651 -0.000676130270 0.00482006812 0.00838195974
## x31 -0.00774318161 -0.003705856571 -0.00417053302 -0.00357092234
## x32 1.00000000000 -0.010375235285 -0.01128368821 -0.00087181275
## x33 -0.01037523529 1.000000000000 -0.00391245676 -0.00364695548
## x34 -0.01128368821 -0.003912456765 1.00000000000 0.00221809494
## x35 -0.00087181275 -0.003646955478 0.00221809494 1.00000000000
## x36 0.00079104947 -0.000559928017 -0.00122949620 0.00188648158
## x37 0.00049650231 0.002733466984 -0.00005889087 0.01599647392
## x38 0.00137233597 0.002306673375 -0.00713603412 0.00526180447
## x39 -0.00103648479 -0.004672264266 -0.00494012101 0.00313977231
## x40 -0.00428471001 0.005674084906 -0.00567439467 0.00440595345
## x41 -0.00004728134 -0.011557294728 0.00133724335 -0.00159332260
## x42 0.00046182697 0.010328381030 0.00525262101 0.00001185324
## x43 -0.00756304339 -0.006220967332 -0.00206071282 -0.01197903115
## x44 -0.00143623759 0.004419443784 -0.00043958837 0.00937915003
## x45 0.00036667234 0.004952062815 -0.00482372388 0.00106896338
## x46 -0.00637518040 -0.000798520765 0.01523766870 -0.00244434887
## x47 -0.00008731304 -0.000967592049 -0.00302950010 0.02130494680
## x48 0.00325148229 -0.001147934023 -0.01693332120 -0.00008199903
## x49 -0.00288777595 0.005301799411 -0.00087146043 0.00252051630
## x50 -0.00227426247 -0.000265707795 0.00252202602 0.00003697320
## x51 -0.00551303001 -0.008037780990 0.00918428702 -0.00454475639
## x52 -0.00372510114 0.004721245218 0.01713062829 -0.00249292719
## x54 0.00142055657 0.000180919669 -0.00365319711 0.00147285435
## x55 0.00617320954 0.000675786149 -0.00098320811 0.00955453794
## x56 0.00057284772 0.001204434399 0.00447409226 0.00281349226
## x57 -0.00430819159 -0.002924523299 0.00283804542 0.00421316586
## x58 0.00456032774 -0.000009894333 0.00697180125 -0.00523808983
## x60 -0.00223473496 -0.008821506004 0.00035794721 0.00622263478
## x61 0.00673985562 -0.006526828754 -0.00057227210 0.00422564565
## x63 -0.00448606323 -0.002943626839 0.00295225282 0.00417917859
## x64 -0.00735865725 0.002269076410 0.00088671532 0.00140576991
## x65 0.00404605875 -0.003585450473 0.00233001651 0.00007411887
## x66 -0.00928573103 0.007399183761 0.00179793052 0.00002371350
## x68 -0.00173045187 -0.003583685565 0.01094703459 0.00002549048
## x69 -0.00455857120 -0.006399106948 0.01423471478 0.01280738593
## x70 -0.00558912661 0.002012552962 -0.00962871786 0.00009745170
## x71 0.00429590252 -0.003054358787 0.00292701675 -0.00001895852
## x72 -0.00085266649 -0.007185406466 -0.00103411083 -0.00208812899
## x73 0.00020577691 0.000850018403 0.00207991273 -0.00698494106
## x74 -0.00012589914 0.008003452990 0.00304862049 -0.00209749081
## x75 0.01207838757 -0.001035304583 -0.01066054710 -0.00935393759
## x76 -0.00223296768 -0.008821060963 0.00035900402 0.00622301693
## x77 -0.00102142190 0.001677434608 -0.01374878343 0.00002572227
## x79 0.00400972441 0.014027321232 -0.00112848845 0.01130968457
## x80 0.00198390931 0.001028217202 0.00708851307 0.00003130560
## x81 -0.00222447250 -0.001459806355 0.00133718212 0.00312888317
## x82 0.00178229164 0.010084452233 0.00103249107 -0.00545048626
## x83 0.00487461695 -0.007483868507 0.00515273781 -0.00494671899
## x84 -0.00774316417 -0.003705948546 -0.00417041226 -0.00357093567
## x85 -0.00928503662 0.007400891542 0.00180045291 0.00002346116
## x86 -0.00539386835 0.006753762404 0.00378526505 0.00527019209
## x87 0.01106442564 0.002074521361 0.00030270634 -0.00221471332
## x88 0.99999956902 -0.010371293137 -0.01128158969 -0.00086346890
## x89 0.01377508165 0.001144840189 -0.00734999887 0.01104040795
## x90 -0.00218027108 0.000061240639 0.00252431474 0.00018216794
## x92 0.00515492439 0.000232393840 -0.00964937767 0.00452358840
## x93 0.00878048376 0.009443421330 -0.00085972853 0.01092085130
## x94 0.00863014554 0.007085304469 -0.00621947071 -0.00608681340
## x95 0.00206444845 -0.016156135196 0.00323768883 0.01285585933
## x96 -0.00563729367 -0.004947124844 0.00518822369 0.00286721336
## x97 0.00670049378 -0.009676138676 0.00616064483 0.00077819831
## x98 -0.00908354659 0.003779891833 0.00517252911 0.01091848619
## x99 -0.00411100821 0.001371551349 0.00485898804 -0.00791386959
## x101 -0.00173954298 0.005248309342 -0.00093441236 -0.00385930890
## x102 0.00077888448 -0.003035257824 -0.01331892962 -0.00244428207
## x103 -0.00957301183 0.000530628224 0.00775767302 0.00562006666
## x104 0.00908902463 0.006601480412 -0.00083399127 0.00004279721
## x105 -0.01277011780 0.005110686932 0.00896236760 0.00539359210
## x106 -0.00494963155 -0.005462416330 -0.00639705076 -0.00020613179
## target -0.01404464784 0.002092522381 0.01482890843 0.00205295156
## x36 x37 x38 x39
## x1 -0.0057834856 -0.00385670589 -0.00470649127 0.000750135236
## x3 -0.0061774517 -0.01667736322 -0.00687030323 0.007311733279
## x4 -0.0020980384 -0.00061121081 0.01053317568 -0.005011135508
## x6 -0.0129414801 0.00292983724 -0.00584730647 0.000538659912
## x7 -0.0027152813 -0.00257241766 -0.00709208081 -0.001246147985
## x8 -0.0053533038 -0.00204362598 -0.00234303334 -0.007362154016
## x9 -0.0005173722 -0.00272613564 -0.00187239938 -0.002768209284
## x10 0.0026555390 0.01279676523 -0.00620068639 0.000363237128
## x11 -0.0109195292 -0.00105554849 0.00109635942 0.002518323298
## x12 -0.0056600291 -0.00351837744 -0.00779005674 -0.004917999217
## x13 0.0056374909 0.00390936897 -0.00144442930 0.006626323228
## x14 -0.0012885175 0.01048589803 -0.00571198956 0.003697413314
## x15 0.0051910278 0.01032409245 -0.01041059453 0.000000123538
## x16 0.0024309080 0.00047000446 0.00299917797 0.003687784207
## x17 0.0100459198 -0.00221777919 -0.00442544136 0.012915742186
## x18 0.0006926434 0.00518465765 -0.01747141295 -0.010491119617
## x19 -0.0071994308 0.00928856771 0.00450749203 0.013271705621
## x20 -0.0003397158 -0.00546480209 0.00918708121 0.002531157176
## x21 -0.0020404419 -0.00003981204 -0.00575447736 0.000363897434
## x22 -0.0010560308 0.00414896879 0.01050391128 0.004768372290
## x23 0.0001162796 -0.00941376522 -0.00209797510 0.005308288094
## x24 0.0001180926 -0.00459725813 0.00738608550 -0.010236263639
## x25 -0.0078734497 -0.00964745449 0.00668005386 0.000791203026
## x26 0.0010168145 0.00120090741 -0.00267035785 0.000698611140
## x29 -0.0007181647 -0.00414198081 0.00747959503 -0.009731037477
## x30 -0.0099284631 -0.00301655093 -0.00667377082 -0.011519019380
## x31 -0.0055125970 0.00563131073 -0.00961271776 -0.006019067881
## x32 0.0007910495 0.00049650231 0.00137233597 -0.001036484789
## x33 -0.0005599280 0.00273346698 0.00230667338 -0.004672264266
## x34 -0.0012294962 -0.00005889087 -0.00713603412 -0.004940121013
## x35 0.0018864816 0.01599647392 0.00526180447 0.003139772309
## x36 1.0000000000 -0.00051744758 -0.00030672745 -0.015775740319
## x37 -0.0005174476 1.00000000000 0.00192816956 0.008146935820
## x38 -0.0003067275 0.00192816956 1.00000000000 -0.003403493336
## x39 -0.0157757403 0.00814693582 -0.00340349334 1.000000000000
## x40 0.0081092591 -0.00453474294 -0.00579023550 0.008675306632
## x41 0.0076937775 -0.00609451484 -0.00370753406 -0.002701069446
## x42 0.0033646717 0.03547342678 0.01813503562 -0.000450550047
## x43 0.0051029785 0.00974329640 -0.01567687307 -0.004349440320
## x44 0.0044744160 0.00731421071 0.00269529223 -0.004099895149
## x45 0.0047984704 0.00666542356 -0.00209501563 -0.003708075122
## x46 -0.0015576085 -0.00099426940 0.00590011498 0.000735895310
## x47 0.0062243819 -0.00371598640 0.01204887931 -0.001808999898
## x48 0.0008962539 0.00457119255 -0.00301838909 -0.009834909109
## x49 -0.0021243728 -0.00019958875 -0.00582501815 0.004293160473
## x50 0.0084961705 0.00369895434 0.00596290007 0.003306726637
## x51 -0.0022471256 -0.00277069243 0.00375841606 -0.003669783682
## x52 -0.0019079677 0.00500140711 0.00163659190 0.000946781832
## x54 -0.0086093569 -0.00112360492 0.00127562205 0.009550228463
## x55 0.0057166449 0.00424612352 0.00636495432 0.000273954225
## x56 -0.0023767627 -0.00641063952 -0.00775660543 0.003363379228
## x57 -0.0073437042 0.00696192450 0.00139493901 -0.005033138792
## x58 0.0025842648 0.01409018434 0.00735988786 -0.002227949764
## x60 -0.0120209015 0.00263883341 -0.00652733521 0.000615041787
## x61 -0.0012220590 -0.00590666813 0.01204779525 0.000787664874
## x63 -0.0074272452 0.00707813205 0.00138348714 -0.005132863866
## x64 -0.0003982945 -0.00397748790 0.00748969219 -0.009674736107
## x65 0.0046326492 0.00029103134 0.00228240316 0.008475622126
## x66 -0.0069604660 -0.00191548592 -0.00261373068 -0.001592447059
## x68 0.0062142203 -0.00216630717 0.00201262247 -0.005046102627
## x69 -0.0074184939 -0.00439598020 -0.00651383053 0.001362925148
## x70 -0.0034221296 0.00055841680 0.00227792609 0.012498690664
## x71 0.0011246115 -0.00070696027 -0.00940922953 -0.002477315116
## x72 -0.0048469066 0.00561350036 -0.00173368757 -0.001755345851
## x73 0.1669782679 0.00563160906 0.00208357127 0.001673769867
## x74 -0.0065817225 -0.00766736134 0.00332093888 0.010541802615
## x75 0.0028847549 -0.00825347043 0.00316496042 -0.005604091742
## x76 -0.0120208692 0.00263986523 -0.00652690656 0.000615066609
## x77 -0.0016932362 -0.00028814488 0.00409144667 -0.004723028676
## x79 -0.0003743254 0.00623522926 -0.00975516164 0.008967502035
## x80 0.0020415176 -0.01037104484 0.00041059314 -0.006317961554
## x81 -0.0061296712 0.00302939059 0.00562670902 -0.007289801939
## x82 0.0115515911 -0.00625398530 0.00285382251 0.010648896130
## x83 0.0130033109 0.00062528635 -0.00532174158 -0.015198617179
## x84 -0.0055125225 0.00563124406 -0.00961264332 -0.006019227936
## x85 -0.0069600771 -0.00191658519 -0.00261295404 -0.001590693508
## x86 -0.0021627063 0.01081618198 -0.00740672030 0.001991917481
## x87 0.0136586243 0.00132949607 -0.01050357150 0.000212540204
## x88 0.0007919388 0.00049838244 0.00137067906 -0.001035428415
## x89 -0.0013596406 0.00381294395 -0.00005842521 0.002457134468
## x90 0.0082146541 0.00387119847 0.00645892740 0.003486056442
## x92 -0.0013057440 0.00424220214 0.01065342171 0.004830769631
## x93 0.0019633256 0.00143294537 -0.00205056912 0.002707328444
## x94 0.0056346263 -0.00199550403 -0.00727757812 0.004733544651
## x95 -0.0018736541 0.00162621810 0.00026372436 0.004933076263
## x96 -0.0076521936 0.00600847522 0.00233525429 -0.005809791892
## x97 -0.0005706166 0.00533733063 0.00445312398 -0.002675336372
## x98 -0.0106332604 -0.01137617607 -0.00186892067 -0.000094395284
## x99 -0.0009733391 -0.00424946046 -0.00543534360 -0.002768284045
## x101 -0.0003414731 -0.00547062350 0.00918172191 0.002527963166
## x102 -0.0014031833 0.00090931883 -0.00154155166 0.004233746204
## x103 0.0006773556 -0.00292491443 0.00488165554 -0.000196271016
## x104 -0.0001390916 0.00069996996 -0.01357176407 0.004063505332
## x105 0.0025797435 0.00558617087 -0.01777770915 -0.011770092586
## x106 -0.0016454848 -0.00853909218 -0.00001037273 0.002490330822
## target 0.0079232026 0.00154185007 -0.02037677474 0.114449779292
## x40 x41 x42 x43
## x1 -0.000471212097 -0.00814909005 0.00969520199 -0.0070989420
## x3 0.001491214520 0.00302520230 0.00587504117 0.0039158576
## x4 -0.001631356864 0.00681793528 0.00781430918 -0.0087046132
## x6 -0.002675175561 0.00509249116 -0.00316904057 0.0018834281
## x7 -0.004182749732 -0.00217791423 -0.00553988663 -0.0018347085
## x8 -0.000520798780 -0.00025631738 0.00311055854 0.0071675711
## x9 -0.012010033312 0.01529308172 -0.00077630966 0.0015686901
## x10 -0.003207175862 -0.00200570674 -0.00775536609 -0.0051590519
## x11 -0.001013351546 -0.00610258757 -0.01106435195 0.0061537913
## x12 0.005235109713 -0.00875807127 -0.00222543030 0.0017221297
## x13 -0.011014579034 0.00198561897 0.01265753846 0.0065231181
## x14 -0.000984216348 -0.00352177606 0.00171624624 -0.0039085924
## x15 0.000660610408 0.00927755141 0.00368711136 -0.0016358195
## x16 0.003451627152 0.00147200728 0.00294883685 0.0042106767
## x17 -0.006160467256 0.00846264013 -0.00052473655 -0.0007572116
## x18 -0.002036204178 0.00117998395 -0.00281386933 -0.0138075669
## x19 0.001900672374 0.00516792313 -0.00310832855 -0.0089372034
## x20 0.003090388653 0.00675872127 0.00946909345 0.0093495787
## x21 0.001582430453 -0.00949770251 0.00215562095 -0.0061259663
## x22 -0.010252940919 -0.00363454066 0.00180488684 0.0039729832
## x23 -0.003227470426 0.00031307507 -0.00820514483 -0.0050855787
## x24 -0.000237305072 0.01266895032 -0.00243359086 0.0015997895
## x25 -0.006207766591 -0.00396870244 -0.00704187341 0.0052743992
## x26 -0.003566354429 -0.00427418147 -0.00952940619 0.0115995162
## x29 -0.000147722686 0.01367227890 -0.00250620603 0.0001827225
## x30 -0.011240765232 -0.00431092015 -0.01305955899 0.0071415134
## x31 -0.001573951160 0.00917729001 0.00531892321 0.6287787260
## x32 -0.004284710013 -0.00004728134 0.00046182697 -0.0075630434
## x33 0.005674084906 -0.01155729473 0.01032838103 -0.0062209673
## x34 -0.005674394669 0.00133724335 0.00525262101 -0.0020607128
## x35 0.004405953447 -0.00159332260 0.00001185324 -0.0119790311
## x36 0.008109259089 0.00769377752 0.00336467169 0.0051029785
## x37 -0.004534742936 -0.00609451484 0.03547342678 0.0097432964
## x38 -0.005790235496 -0.00370753406 0.01813503562 -0.0156768731
## x39 0.008675306632 -0.00270106945 -0.00045055005 -0.0043494403
## x40 1.000000000000 0.00718583647 -0.00123026545 0.0025722282
## x41 0.007185836471 1.00000000000 0.00337464717 0.0027130602
## x42 -0.001230265449 0.00337464717 1.00000000000 0.0001438755
## x43 0.002572228187 0.00271306025 0.00014387552 1.0000000000
## x44 -0.007684587693 0.00738254206 0.00226072317 0.0072357997
## x45 -0.009974422098 0.00699324571 0.01030656168 0.0063263703
## x46 0.012411444170 0.00998375592 0.00089702279 0.0062185903
## x47 0.003151470413 -0.00414510049 0.00565871880 -0.0017292328
## x48 -0.003579430611 -0.00182345772 -0.00125280377 0.0038706617
## x49 0.003634197498 -0.00229340129 -0.00010698550 -0.0001307710
## x50 -0.000470665364 0.00145166053 0.00492867025 0.0038714004
## x51 -0.011136767892 0.00590748075 0.00412809045 0.0013574801
## x52 0.007532235061 0.01351575569 0.00141464249 0.0081513878
## x54 -0.002721692196 0.00308320835 -0.00291925209 0.0001934658
## x55 -0.013177134413 0.00977519367 0.00327668646 -0.0121326650
## x56 0.001856201398 0.00407753033 0.00508550394 -0.0096563712
## x57 0.006221793261 -0.00497700071 -0.00123681573 -0.0009036319
## x58 -0.004567296859 -0.00339844946 0.00998608878 -0.0007381383
## x60 -0.004010054090 0.00437887174 -0.00404386518 0.0023541066
## x61 -0.005751675026 0.00091484602 0.00020298455 -0.0082742379
## x63 0.006167882731 -0.00497902537 -0.00134485410 -0.0007292838
## x64 -0.000217821559 0.01364792129 -0.00251812957 0.0005708883
## x65 0.018684036891 0.14221268454 -0.00107804017 -0.0004806131
## x66 -0.003302895850 -0.00101190577 0.00446548094 -0.0006686640
## x68 0.007567942418 -0.00548667580 0.00469448850 0.0028729318
## x69 -0.000046724913 0.00119122904 -0.00034624009 0.0090382097
## x70 0.006699015778 -0.00203886749 -0.00233066341 -0.0060885046
## x71 -0.002825870971 -0.00102747046 -0.01177389352 -0.0003760487
## x72 0.018145134671 -0.00120048029 -0.00195349288 0.0134104183
## x73 0.008378936786 -0.00107316161 0.00364775811 0.0068610215
## x74 0.001452206895 0.00045325875 -0.00248991710 -0.0079192091
## x75 -0.001510867863 -0.00826618082 -0.00848545472 0.0107513777
## x76 -0.004013885844 0.00438060217 -0.00404328896 0.0023567384
## x77 -0.002469225410 0.00455087730 -0.00624240911 0.0009117302
## x79 -0.009059124949 0.00323013124 -0.00354886170 0.0022135541
## x80 -0.006879871718 -0.00390452268 -0.00032225783 0.0082995477
## x81 -0.000984917630 0.00460689974 -0.00487283895 0.0073425084
## x82 0.001799384192 -0.00119764714 -0.00256028785 0.0032548038
## x83 0.005476595176 -0.00006782043 -0.01459502987 0.0030451572
## x84 -0.001574059348 0.00917747692 0.00531903332 0.6287787652
## x85 -0.003301366782 -0.00101140043 0.00446478017 -0.0006697495
## x86 0.001830225330 -0.00443356943 0.00282595442 -0.0073150975
## x87 -0.000006787911 0.00903500459 -0.00276909688 0.0006570550
## x88 -0.004288543307 -0.00005206408 0.00045185125 -0.0075515252
## x89 0.003413651027 0.01078792231 -0.00059038948 0.0045895739
## x90 -0.001059959998 0.00180377542 0.00504408033 0.0035869456
## x92 -0.010188842541 -0.00365360606 0.00174380380 0.0035467853
## x93 -0.005924125266 -0.01497816535 0.00605183991 -0.0065575914
## x94 0.009397123002 -0.00624334721 -0.00224625017 0.0080838735
## x95 0.007875714198 0.01191536570 -0.00430711648 0.0047553846
## x96 0.003052991272 -0.00324276017 -0.00008491819 -0.0005075609
## x97 -0.008745248302 -0.00626134827 0.00219676665 0.0002484492
## x98 0.000550102433 -0.00693419261 0.00376007405 -0.0117522534
## x99 -0.004211538028 0.00146162334 -0.00416660188 -0.0003684985
## x101 0.003095835475 0.00674656830 0.00946012985 0.0086174299
## x102 0.002651234773 0.00346153241 0.00239766034 -0.0047074981
## x103 -0.000588974537 0.00382102687 -0.00384302716 0.0042705537
## x104 0.004086263178 0.00408363034 -0.00945826325 -0.0023841584
## x105 -0.000248535472 0.00087705359 -0.00298329657 -0.0139208522
## x106 0.005638959863 -0.00663427243 0.00984679052 -0.0039878893
## target 0.058500409189 0.01955612654 -0.01477332912 -0.0162713254
## x44 x45 x46 x47
## x1 -0.00214586870 -0.0095553589 -0.00850435942 0.00058129606
## x3 -0.00962862551 -0.0039141884 -0.00249122875 -0.00446544041
## x4 0.01009667750 0.0028856696 -0.00528315501 -0.00649489897
## x6 -0.00199003249 0.0134194159 0.00485783143 -0.00515011171
## x7 -0.00897077364 -0.0019325636 0.00524254199 0.00602550006
## x8 0.00499257940 -0.0109232975 -0.01731863355 0.00108184142
## x9 -0.00063887230 0.0014832177 0.00710318314 0.01897438071
## x10 0.00482960117 -0.0070019233 -0.00155244427 -0.00085325787
## x11 -0.00328484880 -0.0023849894 -0.00264596650 -0.00432683482
## x12 0.01134100772 -0.0018159585 -0.00652544892 -0.00282174310
## x13 0.00607808517 -0.0090345420 0.00303857527 -0.00742645899
## x14 0.00040428538 0.0074663022 -0.01085590688 0.00815930260
## x15 0.00414261313 -0.0053053809 0.00068991216 0.00129700484
## x16 0.00791442218 -0.0012286287 0.00060423789 -0.00849224116
## x17 -0.00026588334 0.0029457715 0.00064072944 0.00233037555
## x18 -0.00111018743 -0.0002073913 -0.00547686990 -0.01100068212
## x19 0.00024333462 -0.0059196930 -0.00296985866 0.00159679523
## x20 0.00504489933 0.0065096791 -0.00264182062 -0.00415869982
## x21 0.00224853989 0.0061650959 0.00004695759 0.00084285881
## x22 0.00282112520 0.0041934812 -0.00737804965 0.00755189931
## x23 -0.00795543128 -0.0038112186 -0.00119026346 0.00141186431
## x24 0.01741426870 -0.0057322098 -0.00226086037 0.01749535481
## x25 -0.00714709394 0.0065126048 0.00149878043 0.00131214229
## x26 0.00409444418 0.0005126440 -0.00142788435 -0.00684281271
## x29 0.01677375174 -0.0056807586 -0.00132907914 0.01677132198
## x30 -0.00065377041 -0.0023742871 0.00518344601 0.00080433365
## x31 0.00556871680 0.0028086836 0.00616537234 -0.00077844136
## x32 -0.00143623759 0.0003666723 -0.00637518040 -0.00008731304
## x33 0.00441944378 0.0049520628 -0.00079852076 -0.00096759205
## x34 -0.00043958837 -0.0048237239 0.01523766870 -0.00302950010
## x35 0.00937915003 0.0010689634 -0.00244434887 0.02130494680
## x36 0.00447441596 0.0047984704 -0.00155760848 0.00622438194
## x37 0.00731421071 0.0066654236 -0.00099426940 -0.00371598640
## x38 0.00269529223 -0.0020950156 0.00590011498 0.01204887931
## x39 -0.00409989515 -0.0037080751 0.00073589531 -0.00180899990
## x40 -0.00768458769 -0.0099744221 0.01241144417 0.00315147041
## x41 0.00738254206 0.0069932457 0.00998375592 -0.00414510049
## x42 0.00226072317 0.0103065617 0.00089702279 0.00565871880
## x43 0.00723579967 0.0063263703 0.00621859034 -0.00172923279
## x44 1.00000000000 0.0102580379 0.00848039807 -0.00229223342
## x45 0.01025803790 1.0000000000 -0.01506307165 0.00379040385
## x46 0.00848039807 -0.0150630716 1.00000000000 -0.00427261308
## x47 -0.00229223342 0.0037904039 -0.00427261308 1.00000000000
## x48 -0.00064513734 -0.0047355964 -0.00366248017 -0.00065592985
## x49 -0.00017387548 -0.0018370322 -0.00312432042 0.00389112813
## x50 -0.00334172528 -0.0048712593 -0.00626038930 0.01089775767
## x51 0.00297339509 0.0030485253 -0.00780295835 0.00253260259
## x52 0.00978606946 -0.0122984840 0.70554442351 -0.00083364658
## x54 0.00009010889 -0.0043409151 -0.00246939798 -0.00418093230
## x55 -0.00726733759 -0.0018710697 -0.00426462553 0.00443989664
## x56 0.00547413413 0.0026220386 -0.01088152774 0.00397559229
## x57 0.00183504934 -0.0130372569 0.00117716933 -0.00085223491
## x58 0.00830355270 0.0079184200 -0.00237583383 -0.00888698380
## x60 -0.00181832028 0.0127708231 0.00482582025 -0.00482244405
## x61 -0.00237594813 0.0039928988 0.00027272093 -0.00168334783
## x63 0.00184629111 -0.0130901254 0.00122502915 -0.00095635505
## x64 0.01684144563 -0.0058073570 -0.00136506930 0.01675715958
## x65 -0.00249947362 -0.0042831880 -0.01171684353 0.00091120390
## x66 0.00723127710 -0.0014149947 0.00456043457 -0.00721249063
## x68 0.00344011383 -0.0032739168 -0.01432432241 -0.00229306247
## x69 -0.00199149159 -0.0045918264 0.00813536803 -0.00479403980
## x70 -0.00391773188 0.0069063470 -0.00435090691 -0.00528043164
## x71 0.00178714187 -0.0090269376 0.00156198833 -0.00183691675
## x72 -0.00405368523 -0.0029852720 0.00144897262 -0.00412380616
## x73 0.00226898415 -0.0017533886 -0.00133916279 0.00339316059
## x74 0.00849165736 0.0159292408 -0.00165363697 0.00835153940
## x75 0.00216858727 0.0016876846 -0.00306767520 0.00163936482
## x76 -0.00181858265 0.0127674431 0.00482676843 -0.00482259810
## x77 0.00021750792 0.0053440058 -0.00390811880 -0.00137686175
## x79 -0.00127602997 0.0084401707 -0.00317124381 0.00501950343
## x80 -0.00201314978 -0.0023613858 -0.00650489286 -0.00613483733
## x81 0.00393103713 -0.0016301683 0.00711693094 -0.00131110100
## x82 -0.01031055880 -0.0016566013 0.00377450764 0.00567347589
## x83 -0.00936882251 -0.0025616123 -0.00081831598 0.00982322168
## x84 0.00556866369 0.0028087189 0.00616535740 -0.00077833345
## x85 0.00723220997 -0.0014128556 0.00455941086 -0.00721076864
## x86 0.00161348819 0.0091823959 -0.00960332640 0.00867798029
## x87 0.00835112369 -0.0109094729 0.00366840759 0.00471623315
## x88 -0.00143245482 0.0003680328 -0.00637589826 -0.00009276725
## x89 0.01162931274 -0.0022614044 -0.01331880248 0.00537458936
## x90 -0.00285733461 -0.0053147533 -0.00642701190 0.01071645051
## x92 0.00273899843 0.0042182701 -0.00732316118 0.00730669740
## x93 -0.01601919213 0.0002024476 -0.00164099375 0.00581209181
## x94 0.01117235149 0.0006898639 -0.01137082795 -0.01617010870
## x95 -0.00038884619 0.0008188467 0.00532295232 -0.01535829716
## x96 0.00256201928 -0.0117885191 -0.00091662535 -0.00013179740
## x97 0.00607143171 -0.0057786173 0.00618243941 -0.00401580945
## x98 -0.00414659869 0.0109271931 -0.00500755822 -0.00407921191
## x99 -0.00906368571 0.0010754710 -0.01439883257 -0.00072645923
## x101 0.00504617835 0.0065085650 -0.00265339410 -0.00415122466
## x102 0.00633690058 -0.0016191381 0.00078487256 -0.00174162544
## x103 0.00426054093 -0.0045562219 0.00278699253 0.01178587842
## x104 -0.00006066473 0.0057888088 -0.00280838594 0.01127799860
## x105 -0.00242442519 0.0009217907 -0.00608693847 -0.01112038313
## x106 -0.01699722025 -0.0067776791 -0.00362092346 0.00314375494
## target 0.02048342393 -0.1346590433 -0.00219293993 0.00048704355
## x48 x49 x50 x51 x52
## x1 0.01008496281 0.00151407646 0.0062819868 -0.00473011709 -0.0092384744
## x3 -0.00256809561 0.00758743852 -0.0139747698 -0.00156844621 -0.0019108311
## x4 0.00032147208 0.00183465766 0.0075994848 0.00257209023 0.0011220372
## x6 0.00210038415 -0.00357327579 -0.0025781550 0.00495487511 0.0047945713
## x7 0.00644579485 -0.00249166932 0.0107773552 0.00965521570 0.0025410809
## x8 -0.00033764724 -0.00363540544 0.0096227981 0.00342203441 -0.0188767544
## x9 -0.00048540897 0.00650956802 -0.0021103346 0.00515630233 0.0059823785
## x10 0.00576028324 -0.00225025078 -0.0016478909 -0.00210477911 0.0048984301
## x11 0.00089439673 0.01178426610 -0.0034242380 0.00470009117 -0.0013248152
## x12 -0.00480376072 -0.00703574575 0.0040493477 -0.00253237924 -0.0011707895
## x13 -0.01049740283 0.00342301027 -0.0078872947 0.00076829648 0.0028177413
## x14 -0.00986189426 0.00554867347 -0.0026021129 -0.00206618014 -0.0068102751
## x15 -0.01108088029 0.00866202647 0.0058147317 -0.00126322407 0.0037655848
## x16 0.00417885657 0.00466259630 -0.0009924687 -0.00229311568 -0.0063957059
## x17 -0.00412021795 -0.00977672816 0.0032035153 -0.00421932897 0.0007111457
## x18 -0.00130871079 -0.00452666263 0.0016405970 0.00639883782 0.0020111648
## x19 -0.00101750810 -0.00426232688 0.0001544944 0.00349490079 0.0027225700
## x20 0.00106944006 0.00441983026 0.0077699132 -0.01003415196 0.0022771145
## x21 0.00724541648 0.00202653387 -0.0090607002 -0.01435779299 0.0109427923
## x22 0.00134890498 0.00520810055 -0.0063576533 0.00015688919 -0.0005802273
## x23 -0.00755417726 0.00286879389 -0.0012375254 0.00167031834 0.0014112261
## x24 0.00168531364 0.00658027281 -0.0023811518 -0.00553145003 0.0042985435
## x25 -0.00358571845 0.00739927857 -0.0037985363 -0.00085587233 -0.0054310300
## x26 -0.00283887266 -0.00948517427 0.0107585955 -0.00054132161 0.0014548364
## x29 0.00177880347 0.00678472505 -0.0024248353 -0.00588466438 0.0044536061
## x30 0.00070085804 0.00980394988 -0.0105203848 0.01003133858 -0.0082535109
## x31 0.00119630993 -0.00233508002 -0.0035628256 0.00451546144 0.0041721026
## x32 0.00325148229 -0.00288777595 -0.0022742625 -0.00551303001 -0.0037251011
## x33 -0.00114793402 0.00530179941 -0.0002657078 -0.00803778099 0.0047212452
## x34 -0.01693332120 -0.00087146043 0.0025220260 0.00918428702 0.0171306283
## x35 -0.00008199903 0.00252051630 0.0000369732 -0.00454475639 -0.0024929272
## x36 0.00089625386 -0.00212437284 0.0084961705 -0.00224712561 -0.0019079677
## x37 0.00457119255 -0.00019958875 0.0036989543 -0.00277069243 0.0050014071
## x38 -0.00301838909 -0.00582501815 0.0059629001 0.00375841606 0.0016365919
## x39 -0.00983490911 0.00429316047 0.0033067266 -0.00366978368 0.0009467818
## x40 -0.00357943061 0.00363419750 -0.0004706654 -0.01113676789 0.0075322351
## x41 -0.00182345772 -0.00229340129 0.0014516605 0.00590748075 0.0135157557
## x42 -0.00125280377 -0.00010698550 0.0049286702 0.00412809045 0.0014146425
## x43 0.00387066173 -0.00013077097 0.0038714004 0.00135748010 0.0081513878
## x44 -0.00064513734 -0.00017387548 -0.0033417253 0.00297339509 0.0097860695
## x45 -0.00473559637 -0.00183703225 -0.0048712593 0.00304852527 -0.0122984840
## x46 -0.00366248017 -0.00312432042 -0.0062603893 -0.00780295835 0.7055444235
## x47 -0.00065592985 0.00389112813 0.0108977577 0.00253260259 -0.0008336466
## x48 1.00000000000 -0.00675518367 -0.0052622197 -0.01461205235 -0.0014098223
## x49 -0.00675518367 1.00000000000 -0.0057624317 0.00560658148 -0.0015756358
## x50 -0.00526221971 -0.00576243169 1.0000000000 0.00712821522 -0.0087941015
## x51 -0.01461205235 0.00560658148 0.0071282152 1.00000000000 -0.0117725737
## x52 -0.00140982226 -0.00157563582 -0.0087941015 -0.01177257372 1.0000000000
## x54 -0.00295928506 0.00035911193 -0.0022888026 0.00344124715 -0.0020941534
## x55 -0.00379065556 -0.00456022785 -0.0102059461 0.00175318574 -0.0027887237
## x56 -0.00659344248 -0.00033830479 0.0004767743 -0.00192079309 -0.0108468094
## x57 -0.00050916629 -0.00048718736 0.0057585163 -0.00593635739 -0.0007388965
## x58 0.01232791837 -0.00527140677 0.0014916770 0.00935803171 -0.0117104962
## x60 0.00242678488 -0.00383877002 -0.0014893337 0.00443587461 0.0051191326
## x61 0.00290756188 -0.00465740282 0.0106327405 0.00892549052 -0.0052940810
## x63 -0.00037699311 -0.00037008657 0.0056279124 -0.00610418956 -0.0006589726
## x64 0.00228437466 0.00691887726 -0.0022644031 -0.00596356389 0.0044538144
## x65 -0.00611122305 0.00030475939 0.0020844450 -0.00860865063 -0.0101937149
## x66 -0.00003393292 -0.01001600793 -0.0019651338 -0.00055759573 0.0033433250
## x68 -0.00016823846 0.00068727024 0.0067308474 -0.00343988544 -0.0145812747
## x69 -0.00348194841 -0.00474783192 0.0022517384 0.00911878893 0.0062708908
## x70 0.00011000689 -0.00416522621 -0.0012935155 0.00959495140 -0.0029920308
## x71 0.00049102270 0.00076080707 -0.0078205139 -0.00390059741 0.0036196692
## x72 -0.00259712488 0.00042563466 0.0006367332 0.00565379227 -0.0072766548
## x73 -0.00309382767 -0.00059178688 -0.0087184268 -0.00671218321 0.0044625260
## x74 -0.00189668753 -0.00173165181 -0.0027103459 -0.00883394137 -0.0068286175
## x75 0.00663707330 -0.00011870901 -0.0036602641 -0.00140063575 -0.0031823669
## x76 0.00242629722 -0.00383802980 -0.0014894635 0.00443602927 0.0051204895
## x77 -0.00002225455 -0.00200983393 -0.0007576242 -0.00216515955 -0.0042324884
## x79 -0.00083587011 -0.00549110933 0.0016654781 0.00514411647 0.0018669774
## x80 0.00014627918 0.00894830518 -0.0099794608 -0.00605218212 0.0057601776
## x81 -0.00106731249 0.00496733627 -0.0141216796 -0.00325109407 0.0017223128
## x82 -0.00881539058 0.00261383679 -0.0017651893 -0.00182713706 0.0022878490
## x83 -0.00040934829 -0.00468259188 0.0047557437 0.00015962439 -0.0064151616
## x84 0.00119623499 -0.00233505522 -0.0035628119 0.00451527464 0.0041720828
## x85 -0.00003424748 -0.01001730109 -0.0019641847 -0.00055746858 0.0033418291
## x86 -0.00962748745 0.00290851715 -0.0022815388 -0.00092012159 -0.0066849258
## x87 -0.00093804730 0.00488852022 0.0126280508 0.00348023598 0.0026663116
## x88 0.00324845619 -0.00289502422 -0.0022643667 -0.00551270742 -0.0037225067
## x89 0.00544151159 -0.00226187173 -0.0061317860 -0.00253660561 -0.0035395890
## x90 -0.00484926495 -0.00526584414 0.9985249883 0.00745096347 -0.0091932160
## x92 0.00129219204 0.00496935152 -0.0064517063 -0.00009412048 -0.0006936889
## x93 -0.00433094632 0.00193119437 0.0076588229 -0.00191003118 0.0028754830
## x94 0.00109821074 -0.00855288219 -0.0090652502 0.01682214196 -0.0102782061
## x95 -0.00584429471 0.00000828874 0.0015760837 -0.01093796251 0.0038313988
## x96 -0.00439836324 0.00101011141 0.0074813970 0.26085778101 -0.0038190626
## x97 0.00260364397 0.00031854295 0.0040200641 0.00073964745 -0.0014567106
## x98 0.00573344647 -0.00174622965 -0.0067305906 0.00940842321 0.0003758799
## x99 -0.00315828993 -0.00777908312 -0.0029347619 0.00516349105 -0.0159857236
## x101 0.00107382536 0.00442872003 0.0077687677 -0.01004784058 0.0022680791
## x102 -0.00232750119 0.01310014810 -0.0029721948 0.00492290057 -0.0070108700
## x103 -0.00648512729 0.00708933104 -0.0082847474 -0.00566657102 0.0011679234
## x104 0.00109336139 0.00746819551 0.0127287780 -0.00240811312 -0.0016570727
## x105 0.00531007538 -0.00310217256 0.0002719618 0.00379995441 0.0026527962
## x106 0.01542917198 -0.00358382174 -0.0059529511 -0.00524274793 -0.0048820961
## target -0.00363382478 -0.00627007312 -0.0873657660 0.00789883836 -0.0024244373
## x54 x55 x56 x57
## x1 -0.00466173380 -0.0017328745 0.00625065830 -0.0078977906
## x3 0.01707487458 -0.0030614128 0.00113803526 0.0031068119
## x4 0.00539922625 0.0069429131 -0.00089137983 0.0030848809
## x6 0.00975555273 -0.0019618485 0.00306667553 0.0013866772
## x7 -0.00357571391 0.0025064270 0.00610670206 0.0045162741
## x8 0.00610877982 -0.0021416183 -0.00399205339 0.0043196366
## x9 -0.00593664661 -0.0100584737 -0.00349499451 0.0006684662
## x10 0.00300814647 0.0032465747 -0.00971700379 0.0029512707
## x11 -0.01108918586 0.0035575468 0.00001637142 -0.0002771376
## x12 -0.00259140191 0.0052233351 0.00233932322 0.0060874352
## x13 -0.01165685821 0.0018535589 0.00590460432 -0.0123136006
## x14 0.00099115601 0.0172688294 -0.00340278568 0.0066555169
## x15 -0.00492772650 -0.0022616794 0.00283954847 0.0063452529
## x16 -0.01075909333 -0.0101390816 -0.00589634311 0.0038273257
## x17 0.00506608180 0.0003546956 -0.00453814767 0.0016267308
## x18 -0.00151656210 -0.0028372461 0.00882114261 -0.0048421000
## x19 -0.00298978075 0.0077764689 -0.00746666266 0.0107905522
## x20 0.01589530260 0.0120577218 0.00419049558 -0.0018943671
## x21 0.00710936414 0.0037696444 -0.00138687647 0.0037358884
## x22 -0.00158267275 -0.0098012199 -0.00302503110 -0.0009259268
## x23 0.00092724259 0.0044539528 -0.00055417683 -0.0062505012
## x24 -0.00425350529 0.0015763522 -0.00220253922 0.0028588976
## x25 -0.00268096850 -0.0019869267 -0.01288727423 0.0040793740
## x26 -0.00101758017 0.0045126499 0.01659190150 0.0055105282
## x29 -0.00434445384 0.0021066199 -0.00191508650 0.0018362838
## x30 0.00290639420 0.0069440825 -0.00660835339 0.0027307905
## x31 0.00265985098 -0.0083457519 -0.01950560289 -0.0102259945
## x32 0.00142055657 0.0061732095 0.00057284772 -0.0043081916
## x33 0.00018091967 0.0006757861 0.00120443440 -0.0029245233
## x34 -0.00365319711 -0.0009832081 0.00447409226 0.0028380454
## x35 0.00147285435 0.0095545379 0.00281349226 0.0042131659
## x36 -0.00860935694 0.0057166449 -0.00237676267 -0.0073437042
## x37 -0.00112360492 0.0042461235 -0.00641063952 0.0069619245
## x38 0.00127562205 0.0063649543 -0.00775660543 0.0013949390
## x39 0.00955022846 0.0002739542 0.00336337923 -0.0050331388
## x40 -0.00272169220 -0.0131771344 0.00185620140 0.0062217933
## x41 0.00308320835 0.0097751937 0.00407753033 -0.0049770007
## x42 -0.00291925209 0.0032766865 0.00508550394 -0.0012368157
## x43 0.00019346584 -0.0121326650 -0.00965637117 -0.0009036319
## x44 0.00009010889 -0.0072673376 0.00547413413 0.0018350493
## x45 -0.00434091514 -0.0018710697 0.00262203861 -0.0130372569
## x46 -0.00246939798 -0.0042646255 -0.01088152774 0.0011771693
## x47 -0.00418093230 0.0044398966 0.00397559229 -0.0008522349
## x48 -0.00295928506 -0.0037906556 -0.00659344248 -0.0005091663
## x49 0.00035911193 -0.0045602278 -0.00033830479 -0.0004871874
## x50 -0.00228880259 -0.0102059461 0.00047677425 0.0057585163
## x51 0.00344124715 0.0017531857 -0.00192079309 -0.0059363574
## x52 -0.00209415339 -0.0027887237 -0.01084680942 -0.0007388965
## x54 1.00000000000 -0.0068326609 -0.01180903145 0.0097143447
## x55 -0.00683266090 1.0000000000 0.00681171579 0.0009022588
## x56 -0.01180903145 0.0068117158 1.00000000000 0.0060431545
## x57 0.00971434474 0.0009022588 0.00604315446 1.0000000000
## x58 0.00699569472 0.0051367823 -0.00909923848 -0.0006489560
## x60 0.00983817366 -0.0017204984 0.00306080872 0.0011091198
## x61 -0.00131473931 0.0040723269 -0.00383310508 0.0009062965
## x63 0.00976995460 0.0008313579 0.00603490900 0.9998840102
## x64 -0.00453226760 0.0024480765 -0.00199036619 0.0018045974
## x65 -0.00487038250 -0.0089082820 -0.00662947496 0.0062144161
## x66 -0.01205814674 0.0038219844 0.00426410368 0.0057455800
## x68 -0.00582915589 -0.0063634425 -0.00758602024 -0.0053267043
## x69 -0.00068335634 -0.0157303614 -0.00648435844 -0.0044905022
## x70 0.00171766765 0.0057116664 0.00498637867 -0.0038822840
## x71 0.00294505965 -0.0005177186 -0.01227170446 0.0062665964
## x72 0.00076773613 -0.0010222100 -0.00001298569 -0.0079371087
## x73 0.00060227620 -0.0003566853 -0.00363794353 -0.0064826341
## x74 0.00595735788 0.0059808165 0.00795898854 0.0072321901
## x75 -0.01197511551 0.0041954012 0.00399255164 -0.0063650929
## x76 0.00983660777 -0.0017223963 0.00306285126 0.0011049174
## x77 -0.00437531123 -0.0041789763 -0.00604983528 0.0003400360
## x79 -0.00533699217 -0.0079369750 -0.00760620839 0.0017540544
## x80 -0.00155388913 -0.0010296470 0.00111471036 -0.0053148688
## x81 -0.01087255531 -0.0030685587 0.00542953664 0.0058124094
## x82 0.00503868074 0.0056607180 0.00140213836 -0.0110319068
## x83 0.01373579360 0.0039203792 0.00477399282 -0.0009851081
## x84 0.00266002334 -0.0083456912 -0.01950578317 -0.0102260161
## x85 -0.01205864385 0.0038231979 0.00426401871 0.0057462025
## x86 -0.00164340602 0.0165479054 -0.00575818745 0.0056208695
## x87 0.00392041992 0.0048994970 -0.00264694442 -0.0009186441
## x88 0.00141989186 0.0061782847 0.00058886435 -0.0043034882
## x89 -0.01179967726 -0.0016288193 0.00577247050 0.0064578290
## x90 -0.00188106519 -0.0104066618 0.00068894189 0.0056463661
## x92 -0.00176793173 -0.0100095141 -0.00310447615 -0.0009370333
## x93 0.00444997222 -0.0074599133 0.00038509238 -0.0087505582
## x94 -0.00562864632 -0.0088061679 -0.00478078074 0.0114970622
## x95 0.00307017200 0.0050112509 0.00121735617 -0.0012688474
## x96 0.01028953904 0.0013293719 0.00533298430 0.9638069388
## x97 -0.00542982663 -0.0120173299 0.00503950198 0.0093485386
## x98 -0.00068775499 0.0028502455 0.00678514563 -0.0086057774
## x99 0.00054134870 -0.0032422177 -0.00527898639 -0.0158730286
## x101 0.01588599567 0.0120605225 0.00422788260 -0.0018866942
## x102 0.00145734607 0.0008663793 0.00179871533 -0.0009238875
## x103 -0.00910906528 -0.0030753068 -0.00643628489 0.0053854289
## x104 -0.00485075748 -0.0062885687 0.00584815919 0.0052940286
## x105 -0.00224653482 -0.0023639871 0.00969426392 -0.0043476849
## x106 0.00512582340 0.0005481089 -0.00667238282 -0.0026811963
## target 0.04887484233 -0.0132194207 0.03729793409 0.1517785960
## x58 x60 x61 x63 x64
## x1 0.004028694939 0.0026488090 -0.0017207555 -0.0078707725 0.00034310336
## x3 -0.019029849410 -0.0005431027 -0.0012368327 0.0029246726 0.00462976935
## x4 -0.003064308715 0.0016383706 0.0022668844 0.0029333450 0.01268519951
## x6 0.013001233455 0.9958192886 -0.0007733300 0.0015146198 -0.00937156211
## x7 0.000412498421 0.0025788790 0.0028414114 0.0043983755 -0.00115408803
## x8 0.002740323332 0.0057695173 0.0048860822 0.0043451731 -0.00878038526
## x9 -0.004428532212 -0.0039989384 0.0028478646 0.0005887475 -0.00230475734
## x10 -0.000230510945 -0.0024226119 0.0019321724 0.0029523589 -0.00038492634
## x11 0.000032893135 0.0078131645 0.0024155740 -0.0002897083 0.01062748109
## x12 -0.012205434235 0.0030395565 0.0065533155 0.0060557329 0.00902323311
## x13 -0.001325777611 0.0104168962 -0.0067513936 -0.0123963114 -0.00292708688
## x14 0.005832544117 0.0018312531 0.0010059721 0.0067822206 -0.00656895774
## x15 0.003912647044 -0.0036747785 0.0052108627 0.0065024486 0.00225593040
## x16 -0.009277824720 0.0097056617 -0.0003867860 0.0037408315 -0.00300064718
## x17 -0.009502710417 -0.0042115856 0.0006472844 0.0014762331 0.00396549037
## x18 0.001903142970 -0.0040433301 0.0004088480 -0.0049022633 -0.00243799969
## x19 0.006671027814 -0.0007799993 0.0017406407 0.0107561459 -0.00965166993
## x20 0.008370041344 -0.0068199759 0.0044865315 -0.0018843373 0.00568428414
## x21 0.007843167257 0.0020501088 0.0030221951 0.0037092221 0.00587337395
## x22 -0.005000519701 -0.0038371012 -0.0086493146 -0.0009759287 0.00021754632
## x23 -0.011350280130 -0.0048418239 0.0066331721 -0.0062880852 -0.00398303368
## x24 -0.007214231673 -0.0099479941 -0.0055160467 0.0030559895 0.99361598338
## x25 -0.001786301317 -0.0013625976 0.0050294128 0.0039450380 0.00452801775
## x26 -0.000574779818 -0.0014518779 0.0007053683 0.0055329789 0.00101235451
## x29 -0.006883690554 -0.0107804843 -0.0068851972 0.0020282620 0.99944952012
## x30 0.006475218253 -0.0088912422 -0.0164481055 0.0027580608 0.00015358183
## x31 -0.002046464212 -0.0063567221 -0.0023229044 -0.0101819820 0.00838207726
## x32 0.004560327743 -0.0022347350 0.0067398556 -0.0044860632 -0.00735865725
## x33 -0.000009894333 -0.0088215060 -0.0065268288 -0.0029436268 0.00226907641
## x34 0.006971801253 0.0003579472 -0.0005722721 0.0029522528 0.00088671532
## x35 -0.005238089827 0.0062226348 0.0042256456 0.0041791786 0.00140576991
## x36 0.002584264833 -0.0120209015 -0.0012220590 -0.0074272452 -0.00039829454
## x37 0.014090184343 0.0026388334 -0.0059066681 0.0070781320 -0.00397748790
## x38 0.007359887859 -0.0065273352 0.0120477952 0.0013834871 0.00748969219
## x39 -0.002227949764 0.0006150418 0.0007876649 -0.0051328639 -0.00967473611
## x40 -0.004567296859 -0.0040100541 -0.0057516750 0.0061678827 -0.00021782156
## x41 -0.003398449464 0.0043788717 0.0009148460 -0.0049790254 0.01364792129
## x42 0.009986088784 -0.0040438652 0.0002029846 -0.0013448541 -0.00251812957
## x43 -0.000738138307 0.0023541066 -0.0082742379 -0.0007292838 0.00057088829
## x44 0.008303552704 -0.0018183203 -0.0023759481 0.0018462911 0.01684144563
## x45 0.007918420028 0.0127708231 0.0039928988 -0.0130901254 -0.00580735696
## x46 -0.002375833833 0.0048258202 0.0002727209 0.0012250292 -0.00136506930
## x47 -0.008886983802 -0.0048224441 -0.0016833478 -0.0009563550 0.01675715958
## x48 0.012327918371 0.0024267849 0.0029075619 -0.0003769931 0.00228437466
## x49 -0.005271406770 -0.0038387700 -0.0046574028 -0.0003700866 0.00691887726
## x50 0.001491676963 -0.0014893337 0.0106327405 0.0056279124 -0.00226440312
## x51 0.009358031710 0.0044358746 0.0089254905 -0.0061041896 -0.00596356389
## x52 -0.011710496198 0.0051191326 -0.0052940810 -0.0006589726 0.00445381442
## x54 0.006995694721 0.0098381737 -0.0013147393 0.0097699546 -0.00453226760
## x55 0.005136782267 -0.0017204984 0.0040723269 0.0008313579 0.00244807652
## x56 -0.009099238483 0.0030608087 -0.0038331051 0.0060349090 -0.00199036619
## x57 -0.000648955977 0.0011091198 0.0009062965 0.9998840102 0.00180459736
## x58 1.000000000000 0.0134428609 0.0064207841 -0.0006144209 -0.00682600348
## x60 0.013442860939 1.0000000000 -0.0014782363 0.0012364715 -0.01025732228
## x61 0.006420784093 -0.0014782363 1.0000000000 0.0009127578 -0.00652791121
## x63 -0.000614420861 0.0012364715 0.0009127578 1.0000000000 0.00200080144
## x64 -0.006826003475 -0.0102573223 -0.0065279112 0.0020008014 1.00000000000
## x65 -0.005865672960 -0.0014558915 -0.0025644532 0.0061840072 0.00537933865
## x66 0.002952178203 0.0067117160 0.0042208596 0.0055640260 0.00428398364
## x68 0.001258162784 0.0041436926 0.0026181369 -0.0054161487 -0.00224129101
## x69 -0.002897653001 0.0004981779 0.0056354804 -0.0043280687 0.00807828994
## x70 -0.006867554538 -0.0006335368 -0.0046334384 -0.0041316960 -0.00239258449
## x71 0.006081151662 0.0055001150 -0.0037514100 0.0063045470 -0.01117325532
## x72 -0.002330048379 0.0066237705 -0.0057292445 -0.0079878953 0.00184008992
## x73 -0.000708480634 -0.0039795588 -0.0072981514 -0.0065687793 -0.00587150828
## x74 -0.006076280511 -0.0024195178 -0.0023370979 0.0070779733 0.01127006698
## x75 0.006070134252 0.0077007145 0.0019404197 -0.0062865788 0.01606604237
## x76 0.013441208261 0.9999999668 -0.0014782497 0.0012322422 -0.01025953619
## x77 0.002930576345 -0.0009854220 -0.0013574047 0.0004703309 -0.00569064405
## x79 0.003408347788 0.0048346579 0.0174997502 0.0016633824 -0.00849732204
## x80 -0.001230343645 -0.0039115565 0.0005093326 -0.0052654381 0.00273174831
## x81 0.013296319175 0.0146370581 0.0068730340 0.0056529891 -0.00289498622
## x82 0.002409705850 -0.0043171988 0.0116673121 -0.0111144734 -0.00660221301
## x83 -0.005043979277 0.0027289896 0.0028029587 -0.0010693552 0.00923673406
## x84 -0.002046493207 -0.0063567286 -0.0023229135 -0.0101820020 0.00838217443
## x85 0.002954739962 0.0067108778 0.0042209877 0.0055646509 0.00428416844
## x86 0.004446036362 0.0002417232 0.0015562317 0.0057276052 -0.00398382713
## x87 -0.000361641614 0.0070371990 -0.0012236858 -0.0010042929 -0.00049382587
## x88 0.004558614927 -0.0022363650 0.0067397853 -0.0044813458 -0.00735809947
## x89 0.010139273041 -0.0057281217 0.0000367549 0.0065985566 0.00280133830
## x90 0.001592571701 -0.0017660713 0.0111356159 0.0055173650 -0.00254178376
## x92 -0.005136943417 -0.0038890298 -0.0088299939 -0.0009918374 0.00003258859
## x93 -0.004407470898 -0.0046904300 0.0043529416 -0.0087316072 0.00410394574
## x94 0.002961472465 0.0048097460 0.0011110465 0.0115254376 -0.00426324850
## x95 0.002966238531 -0.0002225838 0.0037596310 -0.0012679261 0.00481740289
## x96 0.001840786736 0.0022717008 0.0032426826 0.9636504205 0.00014675290
## x97 -0.006468862164 -0.0038181050 -0.0062021531 0.0094612911 -0.00576687539
## x98 0.003021080371 0.0020048346 -0.0035911041 -0.0086058456 -0.00240904520
## x99 0.006031735734 -0.0090583007 -0.0045464243 -0.0158583998 0.00352144971
## x101 0.008377709808 -0.0068116847 0.0044971858 -0.0018712975 0.00567035541
## x102 -0.007499302647 -0.0069752349 0.0006579387 -0.0009306133 -0.01013722739
## x103 -0.004685677153 0.0040925065 0.0035832205 0.0054243080 -0.00901129374
## x104 -0.006545208740 0.0029667270 0.0088436627 0.0052975769 -0.00346431003
## x105 0.000960378641 -0.0033828542 -0.0007301562 -0.0044002731 -0.00478580304
## x106 -0.000330409736 -0.0026940477 0.0183699034 -0.0025916690 -0.01084570432
## target -0.077446320616 -0.0054944635 0.0642024268 0.1518012735 -0.03294099198
## x65 x66 x68 x69
## x1 -0.004339014425 0.006158695931 0.010984281392 0.00451317989
## x3 -0.007859324459 -0.003912101826 -0.007618269323 -0.00265077468
## x4 -0.002278320576 0.001490632401 -0.006001679223 -0.00115244285
## x6 -0.001603946891 0.006387095025 0.003973227580 0.00004729663
## x7 0.003719297088 0.008180979023 -0.009606738025 0.01394313885
## x8 0.005518412515 0.000021471898 -0.000118210522 -0.00445445887
## x9 0.006967721461 0.000589104612 -0.000214470037 -0.00176221816
## x10 0.006121354962 0.009171875993 0.001596247143 0.00250678010
## x11 0.002940267909 -0.005499541198 -0.018063658265 0.00672686153
## x12 -0.003848854643 -0.008968825181 -0.002813832220 -0.01476868317
## x13 -0.004381397293 -0.003152023928 -0.010375947945 -0.00523679085
## x14 0.000929498585 -0.006819024040 0.006022468570 0.01065638952
## x15 -0.009480586447 0.009032194050 -0.002472441375 -0.00055766212
## x16 -0.004884094374 -0.001363925726 -0.000407680632 -0.00451087231
## x17 0.012057923604 -0.001898793523 -0.004354572658 -0.01114439746
## x18 -0.005134305954 0.011682205685 0.004559075463 -0.00552901906
## x19 0.001423822496 -0.004043897835 0.002962009878 -0.00416901103
## x20 0.000006865111 0.003243668449 0.006854881233 0.00323130712
## x21 0.001561694921 0.009265510346 0.001763983836 0.00323416457
## x22 0.004554794218 -0.000535292724 0.009462982182 0.00783078577
## x23 -0.008235440201 -0.006992788250 0.005130286817 0.00091584463
## x24 0.004988548997 0.005177476192 -0.001604395893 0.00738950379
## x25 0.000624256983 -0.006285015636 0.000043428738 0.00647095610
## x26 -0.003098528922 0.004571637957 0.002409882156 0.00466076790
## x29 0.005483898613 0.004016937648 -0.002266932817 0.00806520134
## x30 -0.003044124714 0.007648033896 0.000878409953 0.00892849053
## x31 -0.001872931761 -0.007770459792 -0.000984331071 0.00973657082
## x32 0.004046058754 -0.009285731026 -0.001730451866 -0.00455857120
## x33 -0.003585450473 0.007399183761 -0.003583685565 -0.00639910695
## x34 0.002330016508 0.001797930518 0.010947034594 0.01423471478
## x35 0.000074118870 0.000023713504 0.000025490484 0.01280738593
## x36 0.004632649183 -0.006960466030 0.006214220289 -0.00741849388
## x37 0.000291031344 -0.001915485917 -0.002166307167 -0.00439598020
## x38 0.002282403164 -0.002613730677 0.002012622473 -0.00651383053
## x39 0.008475622126 -0.001592447059 -0.005046102627 0.00136292515
## x40 0.018684036891 -0.003302895850 0.007567942418 -0.00004672491
## x41 0.142212684538 -0.001011905773 -0.005486675800 0.00119122904
## x42 -0.001078040168 0.004465480940 0.004694488499 -0.00034624009
## x43 -0.000480613104 -0.000668663966 0.002872931842 0.00903820965
## x44 -0.002499473617 0.007231277095 0.003440113835 -0.00199149159
## x45 -0.004283188048 -0.001414994726 -0.003273916752 -0.00459182642
## x46 -0.011716843533 0.004560434572 -0.014324322412 0.00813536803
## x47 0.000911203902 -0.007212490635 -0.002293062470 -0.00479403980
## x48 -0.006111223050 -0.000033932921 -0.000168238457 -0.00348194841
## x49 0.000304759393 -0.010016007932 0.000687270242 -0.00474783192
## x50 0.002084444991 -0.001965133827 0.006730847360 0.00225173845
## x51 -0.008608650627 -0.000557595726 -0.003439885444 0.00911878893
## x52 -0.010193714925 0.003343324993 -0.014581274659 0.00627089079
## x54 -0.004870382503 -0.012058146739 -0.005829155891 -0.00068335634
## x55 -0.008908281976 0.003821984411 -0.006363442520 -0.01573036141
## x56 -0.006629474964 0.004264103675 -0.007586020241 -0.00648435844
## x57 0.006214416120 0.005745579981 -0.005326704285 -0.00449050224
## x58 -0.005865672960 0.002952178203 0.001258162784 -0.00289765300
## x60 -0.001455891537 0.006711715999 0.004143692630 0.00049817788
## x61 -0.002564453209 0.004220859621 0.002618136941 0.00563548039
## x63 0.006184007232 0.005564026040 -0.005416148671 -0.00432806867
## x64 0.005379338649 0.004283983642 -0.002241291012 0.00807828994
## x65 1.000000000000 0.000024285138 0.002425737897 0.00106634874
## x66 0.000024285138 1.000000000000 -0.000081544112 0.00461635018
## x68 0.002425737897 -0.000081544112 1.000000000000 -0.01006294067
## x69 0.001066348740 0.004616350177 -0.010062940670 1.00000000000
## x70 -0.001223471399 0.000004239956 -0.000077473251 -0.00592647717
## x71 -0.003709503321 -0.000268286335 -0.000047413987 0.00574591680
## x72 0.003402867168 0.007704151291 0.001804661006 0.00245347613
## x73 0.006040621576 -0.013171337886 0.008750498577 0.00239731274
## x74 -0.001633865586 -0.003348150768 0.000718949785 -0.00039036288
## x75 -0.001708121911 -0.001779471604 -0.008814446338 0.00515595640
## x76 -0.001455445805 0.006710249174 0.004143683598 0.00049823168
## x77 -0.005815444665 0.000512393198 0.000003229365 0.00589136336
## x79 -0.000038569042 0.004091411386 0.006386841643 -0.00764229262
## x80 0.000223700609 0.000322946184 0.000016531532 0.00535302093
## x81 -0.005230978473 -0.002505365101 0.003917320917 -0.00285813404
## x82 -0.011651055758 -0.013065799209 -0.002690129485 0.00466507288
## x83 -0.006967850323 -0.008898099084 0.004421077365 -0.00569300076
## x84 -0.001872837176 -0.007770405277 -0.000984195989 0.00973661493
## x85 0.000025007487 0.999999984791 -0.000081945675 0.00461666405
## x86 0.000129689882 -0.007680858685 0.005934587959 0.00918610090
## x87 0.006041417006 0.005559365320 0.002782307902 -0.00536260038
## x88 0.004043914307 -0.009281650710 -0.001726426606 -0.00455467993
## x89 -0.002673561352 0.007986139389 -0.003828258314 -0.00302128119
## x90 0.001875319469 -0.002084475714 0.006455578026 0.00177360295
## x92 0.004702352186 -0.000524967266 0.009398112166 0.00766408050
## x93 -0.002046697912 0.002741919469 0.000887849482 -0.00714165543
## x94 -0.000773788380 0.007467290100 0.008207481275 -0.00439412850
## x95 0.003651084718 -0.004218744166 -0.003956905341 0.01074265929
## x96 0.003709748703 0.005434477381 -0.006075489981 -0.00187663823
## x97 -0.012677409410 -0.001599104817 -0.004038602924 -0.00367379902
## x98 -0.003043882903 -0.000877389551 -0.002122762481 -0.00725089437
## x99 -0.001816266772 -0.003397402246 -0.008039369338 0.00129412422
## x101 0.000010817109 0.003248184086 0.006850376885 0.00322287984
## x102 -0.007017826204 0.002491136515 -0.000978993955 0.00549891941
## x103 0.006439106024 0.001639231804 -0.011866735705 -0.00828450347
## x104 0.002693492877 -0.001868621158 -0.001123574062 -0.00025897284
## x105 -0.005480463931 0.010660939433 0.004918199501 -0.00620553871
## x106 -0.009580900941 -0.004521281815 -0.000116655861 0.01318885878
## target 0.021638392410 -0.004579359518 0.003677938720 0.03393926313
## x70 x71 x72 x73
## x1 -0.003460667973 -0.004393207537 0.00285234284 -0.0042772364
## x3 0.006871526512 0.007121280875 -0.01299732440 0.0023083419
## x4 0.011382057455 -0.007198555139 -0.00558285124 -0.0089310968
## x6 -0.001291190825 0.005856470488 0.00555791202 -0.0042762936
## x7 0.003555301401 0.004534235989 -0.00697743248 -0.0033298162
## x8 0.000008868438 -0.000030141973 -0.00183127996 -0.0083742509
## x9 -0.000798505543 -0.000152331680 0.00337751399 -0.0042020662
## x10 -0.003537613627 0.003635125660 0.00991514707 -0.0073344554
## x11 0.016178017321 -0.002895322808 0.00891887241 0.0014191212
## x12 -0.019009841107 -0.003990458123 0.00616544034 0.0052969240
## x13 -0.009430609539 0.006891728836 0.00169984059 -0.0004065870
## x14 -0.003083114341 -0.006310144790 0.00800765914 -0.0011824910
## x15 0.010749758628 -0.003684818154 -0.00765913352 -0.0030810794
## x16 0.000894308061 -0.004064125663 0.00271307321 -0.0016241540
## x17 -0.005896562133 -0.000776507143 -0.00013105057 0.0066553650
## x18 0.005166418299 0.013521858967 0.00563800567 0.0055683600
## x19 0.006913512583 -0.002160355020 0.00975799877 -0.0103714840
## x20 0.005528408992 0.000105038521 -0.01464914276 0.0058654458
## x21 -0.001244493433 0.013942619527 -0.00379791352 0.0019380306
## x22 -0.000288800593 0.005955256194 -0.00095757771 -0.0013660287
## x23 0.004397993384 0.001220182785 -0.00611991707 -0.0022077419
## x24 -0.003033475959 -0.011903752610 0.00181291016 -0.0066589853
## x25 0.016585971373 0.008077387607 0.01061172917 0.0011137364
## x26 0.002747129578 0.000257218235 -0.00141454551 -0.0070352720
## x29 -0.002549294896 -0.011242496037 0.00214926749 -0.0052562072
## x30 -0.001822310963 -0.001569772711 -0.00663784016 -0.0016618977
## x31 -0.004758929463 -0.004061506665 0.01035615109 0.0089657773
## x32 -0.005589126608 0.004295902521 -0.00085266649 0.0002057769
## x33 0.002012552962 -0.003054358787 -0.00718540647 0.0008500184
## x34 -0.009628717860 0.002927016751 -0.00103411083 0.0020799127
## x35 0.000097451702 -0.000018958519 -0.00208812899 -0.0069849411
## x36 -0.003422129583 0.001124611456 -0.00484690656 0.1669782679
## x37 0.000558416799 -0.000706960272 0.00561350036 0.0056316091
## x38 0.002277926086 -0.009409229530 -0.00173368757 0.0020835713
## x39 0.012498690664 -0.002477315116 -0.00175534585 0.0016737699
## x40 0.006699015778 -0.002825870971 0.01814513467 0.0083789368
## x41 -0.002038867493 -0.001027470464 -0.00120048029 -0.0010731616
## x42 -0.002330663406 -0.011773893525 -0.00195349288 0.0036477581
## x43 -0.006088504639 -0.000376048721 0.01341041829 0.0068610215
## x44 -0.003917731881 0.001787141871 -0.00405368523 0.0022689841
## x45 0.006906347005 -0.009026937588 -0.00298527195 -0.0017533886
## x46 -0.004350906914 0.001561988333 0.00144897262 -0.0013391628
## x47 -0.005280431643 -0.001836916749 -0.00412380616 0.0033931606
## x48 0.000110006894 0.000491022696 -0.00259712488 -0.0030938277
## x49 -0.004165226207 0.000760807070 0.00042563466 -0.0005917869
## x50 -0.001293515451 -0.007820513937 0.00063673321 -0.0087184268
## x51 0.009594951395 -0.003900597406 0.00565379227 -0.0067121832
## x52 -0.002992030835 0.003619669231 -0.00727665484 0.0044625260
## x54 0.001717667652 0.002945059650 0.00076773613 0.0006022762
## x55 0.005711666422 -0.000517718601 -0.00102220999 -0.0003566853
## x56 0.004986378674 -0.012271704464 -0.00001298569 -0.0036379435
## x57 -0.003882284046 0.006266596383 -0.00793710870 -0.0064826341
## x58 -0.006867554538 0.006081151662 -0.00233004838 -0.0007084806
## x60 -0.000633536760 0.005500114994 0.00662377054 -0.0039795588
## x61 -0.004633438365 -0.003751410029 -0.00572924446 -0.0072981514
## x63 -0.004131696038 0.006304547048 -0.00798789529 -0.0065687793
## x64 -0.002392584494 -0.011173255322 0.00184008992 -0.0058715083
## x65 -0.001223471399 -0.003709503321 0.00340286717 0.0060406216
## x66 0.000004239956 -0.000268286335 0.00770415129 -0.0131713379
## x68 -0.000077473251 -0.000047413987 0.00180466101 0.0087504986
## x69 -0.005926477167 0.005745916797 0.00245347613 0.0023973127
## x70 1.000000000000 -0.000001901564 -0.00072070885 0.0029059563
## x71 -0.000001901564 1.000000000000 0.00555100387 0.0033265996
## x72 -0.000720708854 0.005551003868 1.00000000000 0.0007137972
## x73 0.002905956332 0.003326599609 0.00071379716 1.0000000000
## x74 -0.003615167797 -0.008375390807 -0.00116963418 -0.0029420450
## x75 -0.002299300275 0.003332236364 0.00368535632 -0.0021385405
## x76 -0.000634448278 0.005500279940 0.00662220981 -0.0039794473
## x77 0.000303853118 0.000016778705 0.00378654579 -0.0057493996
## x79 0.003033475662 0.006563706931 -0.00201640595 0.0018948156
## x80 0.000959977024 -0.000098872799 -0.00362633737 -0.0101338328
## x81 -0.005823269481 0.007906725758 -0.00384577285 0.0028033506
## x82 0.001712036434 -0.003586398549 -0.00369796175 -0.0148558309
## x83 0.001485468105 -0.001369168856 0.00302947159 -0.0054133931
## x84 -0.004759034298 -0.004061357483 0.01035609695 0.0089657570
## x85 0.000004387386 -0.000268851100 0.00770306348 -0.0131720140
## x86 -0.003230341716 -0.006134762619 0.00853233252 -0.0027320675
## x87 -0.000549042552 0.007802027792 0.00105075467 0.0016979565
## x88 -0.005586288793 0.004296056612 -0.00085436335 0.0001989202
## x89 -0.000729429002 0.000766056911 -0.00650306436 -0.0068774311
## x90 -0.000835769281 -0.007783566929 0.00128709978 -0.0088066112
## x92 -0.000286604479 0.005949864747 -0.00118396614 -0.0013378037
## x93 0.002111686507 0.002404753355 -0.00232533031 0.0045794039
## x94 0.003237873002 -0.005437073570 0.00313814445 0.0035105714
## x95 0.000782605535 0.000974049011 -0.00165609985 0.0129418619
## x96 -0.001194781207 0.005028242312 -0.00613113754 -0.0080640135
## x97 -0.000068888333 0.001346294161 0.00652977091 0.0083045053
## x98 -0.006755801872 0.003394798757 0.00673608697 -0.0006790934
## x99 0.006629451234 -0.012840966750 0.00441725441 -0.0069294815
## x101 0.005519566716 0.000119329422 -0.01466961350 0.0058480186
## x102 -0.001508643658 0.002921485066 -0.00549601699 -0.0004996214
## x103 0.002646407536 -0.002737358013 -0.00811428741 -0.0068864498
## x104 -0.000149732669 0.001595242121 0.00222521254 0.0139998646
## x105 0.003773582158 0.013292565671 0.00580264588 0.0057409696
## x106 -0.004031415852 -0.001163335545 -0.00658826979 0.0021417634
## target -0.004857207708 0.000548934218 0.01188435440 0.0031801763
## x74 x75 x76 x77
## x1 -0.00888740401 -0.01022232412 0.0026442500 0.007360383691
## x3 -0.00478557221 -0.00283551674 -0.0005420775 -0.010698830487
## x4 0.00121135553 0.00290804884 0.0016404973 0.001269856752
## x6 -0.00258966068 0.00848067461 0.9958191329 -0.000865801247
## x7 -0.00258116156 0.00383489664 0.0025772145 0.000759078922
## x8 -0.00262412456 -0.00737545849 0.0057688476 0.000057143098
## x9 -0.00509688628 0.00142208124 -0.0039983154 -0.000415145676
## x10 -0.00904985235 0.00075909555 -0.0024234195 0.004800670597
## x11 0.01087375848 -0.00352096124 0.0078113888 -0.002372531737
## x12 0.00195774798 -0.00412616278 0.0030412113 -0.005429144268
## x13 -0.00520809340 -0.00432361410 0.0104134633 -0.010270509694
## x14 -0.00007245535 -0.00464059215 0.0018300807 0.005541713677
## x15 -0.01142957066 0.00764919919 -0.0036727628 0.003812556466
## x16 0.00559041076 -0.00202672271 0.0097075558 0.007611009900
## x17 0.01223509414 -0.00684095077 -0.0042123108 0.001099442176
## x18 -0.00996455018 0.01048579500 -0.0040410196 -0.005041194206
## x19 -0.00643444254 0.00378769716 -0.0007814087 -0.001705237463
## x20 0.00708276858 0.11524829186 -0.0068205308 0.000225148473
## x21 0.01573727519 -0.01258460380 0.0020505614 -0.005662492242
## x22 0.00022795502 0.00597101367 -0.0038364556 0.003196232252
## x23 0.00564979939 0.00322380305 -0.0048400958 -0.000677649112
## x24 0.01107316200 0.01595730335 -0.0099503358 -0.005833825435
## x25 -0.00436416250 -0.00232723864 -0.0013628475 0.007206725848
## x26 0.00718838035 -0.00327925460 -0.0014492180 -0.009419455723
## x29 0.01113547779 0.01647229885 -0.0107827497 -0.005723447972
## x30 -0.00457877851 -0.00386041859 -0.0088922666 0.000442123746
## x31 -0.01144154621 0.00841161067 -0.0063573565 0.007112725259
## x32 -0.00012589914 0.01207838757 -0.0022329677 -0.001021421897
## x33 0.00800345299 -0.00103530458 -0.0088210610 0.001677434608
## x34 0.00304862049 -0.01066054710 0.0003590040 -0.013748783429
## x35 -0.00209749081 -0.00935393759 0.0062230169 0.000025722274
## x36 -0.00658172254 0.00288475488 -0.0120208692 -0.001693236174
## x37 -0.00766736134 -0.00825347043 0.0026398652 -0.000288144876
## x38 0.00332093888 0.00316496042 -0.0065269066 0.004091446667
## x39 0.01054180262 -0.00560409174 0.0006150666 -0.004723028676
## x40 0.00145220690 -0.00151086786 -0.0040138858 -0.002469225410
## x41 0.00045325875 -0.00826618082 0.0043806022 0.004550877297
## x42 -0.00248991710 -0.00848545472 -0.0040432890 -0.006242409114
## x43 -0.00791920912 0.01075137768 0.0023567384 0.000911730231
## x44 0.00849165736 0.00216858727 -0.0018185826 0.000217507918
## x45 0.01592924081 0.00168768463 0.0127674431 0.005344005779
## x46 -0.00165363697 -0.00306767520 0.0048267684 -0.003908118800
## x47 0.00835153940 0.00163936482 -0.0048225981 -0.001376861748
## x48 -0.00189668753 0.00663707330 0.0024262972 -0.000022254548
## x49 -0.00173165181 -0.00011870901 -0.0038380298 -0.002009833931
## x50 -0.00271034590 -0.00366026413 -0.0014894635 -0.000757624209
## x51 -0.00883394137 -0.00140063575 0.0044360293 -0.002165159549
## x52 -0.00682861746 -0.00318236694 0.0051204895 -0.004232488423
## x54 0.00595735788 -0.01197511551 0.0098366078 -0.004375311229
## x55 0.00598081649 0.00419540115 -0.0017223963 -0.004178976317
## x56 0.00795898854 0.00399255164 0.0030628513 -0.006049835279
## x57 0.00723219007 -0.00636509288 0.0011049174 0.000340036037
## x58 -0.00607628051 0.00607013425 0.0134412083 0.002930576345
## x60 -0.00241951781 0.00770071446 0.9999999668 -0.000985422036
## x61 -0.00233709793 0.00194041967 -0.0014782497 -0.001357404693
## x63 0.00707797327 -0.00628657882 0.0012322422 0.000470330883
## x64 0.01127006698 0.01606604237 -0.0102595362 -0.005690644049
## x65 -0.00163386559 -0.00170812191 -0.0014554458 -0.005815444665
## x66 -0.00334815077 -0.00177947160 0.0067102492 0.000512393198
## x68 0.00071894979 -0.00881444634 0.0041436836 0.000003229365
## x69 -0.00039036288 0.00515595640 0.0004982317 0.005891363359
## x70 -0.00361516780 -0.00229930028 -0.0006344483 0.000303853118
## x71 -0.00837539081 0.00333223636 0.0055002799 0.000016778705
## x72 -0.00116963418 0.00368535632 0.0066222098 0.003786545786
## x73 -0.00294204503 -0.00213854052 -0.0039794473 -0.005749399619
## x74 1.00000000000 -0.00182396747 -0.0024204276 -0.000054842248
## x75 -0.00182396747 1.00000000000 0.0077005933 0.003504526486
## x76 -0.00242042764 0.00770059325 1.0000000000 -0.000985025281
## x77 -0.00005484225 0.00350452649 -0.0009850253 1.000000000000
## x79 -0.00775959315 -0.00376715375 0.0048333070 -0.000122896174
## x80 -0.00708492420 -0.00507163154 -0.0039115838 -0.000023358624
## x81 0.00038300499 -0.00291187661 0.0146377324 -0.003179269472
## x82 0.00471802487 -0.00877279951 -0.0043166164 0.003888416237
## x83 0.00023417864 0.00673731760 0.0027309450 0.006286047703
## x84 -0.01144149910 0.00841158126 -0.0063573630 0.007112662257
## x85 -0.00334802047 -0.00177987186 0.0067094107 0.000513558694
## x86 0.00168356603 -0.00478586039 0.0002408367 0.005363626623
## x87 -0.00794846206 -0.00757036242 0.0070376233 -0.000749605674
## x88 -0.00011986323 0.01207437378 -0.0022345952 -0.001029473458
## x89 -0.00221613789 -0.00107401735 -0.0057281446 0.009430468128
## x90 -0.00211409964 -0.00342891143 -0.0017661891 -0.000998239649
## x92 0.00003180002 0.00606569944 -0.0038883289 0.003195986493
## x93 0.00509657404 0.00422596102 -0.0046914633 0.009387606329
## x94 -0.00863650824 0.00491613049 0.0048090500 0.007456035437
## x95 0.00791840775 -0.00004156852 -0.0002199807 -0.007608071814
## x96 0.00463959124 -0.00650831013 0.0022676930 -0.000252426266
## x97 0.00027792651 -0.00395545357 -0.0038185862 0.000431265632
## x98 -0.00512399651 0.00116227467 0.0020041001 -0.004854515390
## x99 -0.01050076415 0.01295481706 -0.0090571508 0.004996744504
## x101 0.00708863885 0.11524039360 -0.0068122425 0.000217341474
## x102 -0.00067242031 0.00419119426 -0.0069763579 -0.005183261354
## x103 0.00065331686 0.00155118005 0.0040931151 -0.003562686439
## x104 -0.00793059828 -0.00498403569 0.0029681251 -0.000046953808
## x105 -0.00927725635 0.00945014645 -0.0033805739 -0.005238202082
## x106 0.00027315884 -0.00050953875 -0.0026926660 0.000385066370
## target -0.01720474421 -0.15597283596 -0.0054959164 -0.002157421740
## x79 x80 x81 x82
## x1 -0.00632287524 0.00033712995 -0.0028922159 -0.00542313485
## x3 -0.00490190023 -0.00319982553 0.0013415510 -0.01233812111
## x4 0.00007580089 -0.00801282265 -0.0114828551 -0.00087689755
## x6 0.00416514940 -0.00470130297 0.0148478206 -0.00461983861
## x7 0.00456621558 -0.00029064278 0.0077728785 -0.00370807064
## x8 0.00140217691 -0.00005192247 0.0025041103 0.00942548357
## x9 0.00404270193 0.00007816811 -0.0113817573 -0.00756202509
## x10 0.00761349375 -0.00238691919 0.0008950053 -0.00630038383
## x11 -0.00590974635 0.00370404457 -0.0104250915 -0.01137233139
## x12 0.00145041636 -0.00104351101 0.0063841840 0.00508571926
## x13 -0.00258595917 -0.00670335170 -0.0071544108 -0.01631469054
## x14 -0.00462782863 -0.00412480389 -0.0016561372 0.00573777528
## x15 0.01038488984 0.00266074233 0.0032506663 -0.00398956759
## x16 0.01025344520 0.00085978721 -0.0079173791 0.00501055839
## x17 0.00397989420 0.00049500497 0.0088033213 -0.00019008925
## x18 0.00737696382 -0.00733205957 -0.0065657756 0.00181673576
## x19 -0.00369666331 -0.00575418138 0.0051541208 -0.00629936047
## x20 0.00124573917 -0.00241465778 -0.0022492997 -0.00143142162
## x21 -0.00492144121 0.00994004752 0.0020946592 0.00806964682
## x22 0.00324572138 0.00439191632 -0.0055375985 -0.00879022669
## x23 -0.00291093506 0.00625542373 -0.0139273110 0.00431618734
## x24 -0.00887366904 0.00377626619 -0.0033975046 -0.00614357281
## x25 0.00180437564 -0.00630117926 0.0115662515 0.00978451670
## x26 0.01580437245 0.00868509097 0.0144045133 -0.00006336198
## x29 -0.00868948321 0.00269502008 -0.0028142611 -0.00678624754
## x30 -0.00727708019 0.00473182625 -0.0042868946 0.00392887301
## x31 -0.00025980145 0.00453868726 0.0135203475 -0.00074524063
## x32 0.00400972441 0.00198390931 -0.0022244725 0.00178229164
## x33 0.01402732123 0.00102821720 -0.0014598064 0.01008445223
## x34 -0.00112848845 0.00708851307 0.0013371821 0.00103249107
## x35 0.01130968457 0.00003130560 0.0031288832 -0.00545048626
## x36 -0.00037432544 0.00204151756 -0.0061296712 0.01155159113
## x37 0.00623522926 -0.01037104484 0.0030293906 -0.00625398530
## x38 -0.00975516164 0.00041059314 0.0056267090 0.00285382251
## x39 0.00896750203 -0.00631796155 -0.0072898019 0.01064889613
## x40 -0.00905912495 -0.00687987172 -0.0009849176 0.00179938419
## x41 0.00323013124 -0.00390452268 0.0046068997 -0.00119764714
## x42 -0.00354886170 -0.00032225783 -0.0048728389 -0.00256028785
## x43 0.00221355408 0.00829954769 0.0073425084 0.00325480378
## x44 -0.00127602997 -0.00201314978 0.0039310371 -0.01031055880
## x45 0.00844017073 -0.00236138581 -0.0016301683 -0.00165660133
## x46 -0.00317124381 -0.00650489286 0.0071169309 0.00377450764
## x47 0.00501950343 -0.00613483733 -0.0013111010 0.00567347589
## x48 -0.00083587011 0.00014627918 -0.0010673125 -0.00881539058
## x49 -0.00549110933 0.00894830518 0.0049673363 0.00261383679
## x50 0.00166547810 -0.00997946076 -0.0141216796 -0.00176518934
## x51 0.00514411647 -0.00605218212 -0.0032510941 -0.00182713706
## x52 0.00186697741 0.00576017764 0.0017223128 0.00228784904
## x54 -0.00533699217 -0.00155388913 -0.0108725553 0.00503868074
## x55 -0.00793697503 -0.00102964704 -0.0030685587 0.00566071799
## x56 -0.00760620839 0.00111471036 0.0054295366 0.00140213836
## x57 0.00175405438 -0.00531486884 0.0058124094 -0.01103190678
## x58 0.00340834779 -0.00123034364 0.0132963192 0.00240970585
## x60 0.00483465793 -0.00391155650 0.0146370581 -0.00431719875
## x61 0.01749975018 0.00050933263 0.0068730340 0.01166731214
## x63 0.00166338243 -0.00526543813 0.0056529891 -0.01111447337
## x64 -0.00849732204 0.00273174831 -0.0028949862 -0.00660221301
## x65 -0.00003856904 0.00022370061 -0.0052309785 -0.01165105576
## x66 0.00409141139 0.00032294618 -0.0025053651 -0.01306579921
## x68 0.00638684164 0.00001653153 0.0039173209 -0.00269012949
## x69 -0.00764229262 0.00535302093 -0.0028581340 0.00466507288
## x70 0.00303347566 0.00095997702 -0.0058232695 0.00171203643
## x71 0.00656370693 -0.00009887280 0.0079067258 -0.00358639855
## x72 -0.00201640595 -0.00362633737 -0.0038457728 -0.00369796175
## x73 0.00189481560 -0.01013383283 0.0028033506 -0.01485583090
## x74 -0.00775959315 -0.00708492420 0.0003830050 0.00471802487
## x75 -0.00376715375 -0.00507163154 -0.0029118766 -0.00877279951
## x76 0.00483330698 -0.00391158375 0.0146377324 -0.00431661641
## x77 -0.00012289617 -0.00002335862 -0.0031792695 0.00388841624
## x79 1.00000000000 -0.00218796624 -0.0010370795 -0.00024376971
## x80 -0.00218796624 1.00000000000 -0.0032526875 -0.01201216619
## x81 -0.00103707946 -0.00325268745 1.0000000000 0.00237766545
## x82 -0.00024376971 -0.01201216619 0.0023776655 1.00000000000
## x83 -0.01148044208 -0.00248574640 -0.0009104429 0.01143051864
## x84 -0.00025981332 0.00453865590 0.0135205375 -0.00074507088
## x85 0.00409151189 0.00032246857 -0.0025072455 -0.01306750411
## x86 -0.00635433158 -0.00401654573 -0.0023613059 0.00364797255
## x87 0.00446092505 -0.00802410727 -0.0165265134 -0.00527434817
## x88 0.00402396710 0.00199126584 -0.0022116851 0.00178216833
## x89 0.00596685381 0.00550124557 0.0016100095 0.00170060320
## x90 0.00166278706 -0.01024160237 -0.0141754847 -0.00182281454
## x92 0.00303404070 0.00439050466 -0.0054752975 -0.00899813781
## x93 0.00271406872 -0.00185123990 0.0081735406 -0.00208179044
## x94 -0.01486055913 -0.00464614990 -0.0059777170 0.00412700220
## x95 0.00266807842 -0.00796358432 0.0084961590 -0.00648723075
## x96 0.00309059088 -0.00674314091 0.0047518455 -0.01114899913
## x97 0.00001251808 0.00361842810 0.0066254867 -0.01447458206
## x98 -0.01121613943 0.00370273493 -0.0006309387 -0.00101052579
## x99 0.01476265257 -0.00303063150 -0.0038736579 -0.00883543285
## x101 0.00123995550 -0.00242294186 -0.0022659421 -0.00142951252
## x102 0.00714368550 0.00031844704 0.0102523202 -0.00603988706
## x103 0.00231697755 -0.00686094559 -0.0054163930 -0.00057593167
## x104 0.00329283084 -0.00161846987 -0.0016893885 -0.00586553605
## x105 0.00601265128 -0.00540319967 -0.0068426322 -0.00165644735
## x106 -0.00388149663 -0.00277732769 0.0012607434 -0.00413583597
## target -0.00196704833 0.00296827858 0.0167311137 -0.10515973790
## x83 x84 x85 x86
## x1 -0.00381751980 -0.0105298658 0.006157356560 -0.00147534799
## x3 -0.00210767433 0.0031676871 -0.003913341250 0.00104551514
## x4 -0.00002180066 -0.0042703979 0.001490532477 -0.00005760458
## x6 0.00235109464 -0.0058738066 0.006386213728 0.00010687579
## x7 -0.00534468710 -0.0019897981 0.008180112507 0.00231378205
## x8 0.00043917358 0.0066537847 0.000022086456 -0.01054890700
## x9 0.00863183873 -0.0012583145 0.000589524969 0.00699496194
## x10 -0.00108731360 0.0035335158 0.009173291868 0.00190066297
## x11 -0.00598667467 0.0048313049 -0.005499772974 0.01695403865
## x12 0.00207218428 0.0055136418 -0.008970664534 -0.00014418637
## x13 -0.00165416904 0.0030869580 -0.003151938265 -0.00745111224
## x14 -0.00993980638 0.0004487740 -0.006818364597 0.97545766052
## x15 0.00321113844 0.0071954275 0.009032123225 -0.00764958545
## x16 -0.00748404142 0.0011062591 -0.001362616986 0.00016974239
## x17 -0.00859560568 0.0003477965 -0.001897103737 -0.00604277237
## x18 0.00415807117 -0.0070272850 0.011683290426 -0.00335315217
## x19 -0.00402155925 -0.0061857744 -0.004044651176 0.00141296589
## x20 0.00242503340 0.0043525833 0.003242723859 -0.00131186627
## x21 -0.00750369431 -0.0144400338 0.009266310889 0.00230707844
## x22 0.00686237553 0.0024207953 -0.000534006491 0.00084562863
## x23 0.00526493474 -0.0057988099 -0.006992484058 -0.00922456257
## x24 0.00786892672 0.0086580116 0.005177596451 -0.00366317117
## x25 -0.00599802548 0.0005457149 -0.006285374472 -0.00967340516
## x26 0.00361172925 0.0056120241 0.004571555583 -0.00191270067
## x29 0.00916964708 0.0081140892 0.004017051528 -0.00401682050
## x30 0.00494965197 0.0002832284 0.007646915422 -0.01202231666
## x31 -0.00309042223 0.9999999999 -0.007770360337 -0.00033316674
## x32 0.00487461695 -0.0077431642 -0.009285036624 -0.00539386835
## x33 -0.00748386851 -0.0037059485 0.007400891542 0.00675376240
## x34 0.00515273781 -0.0041704123 0.001800452907 0.00378526505
## x35 -0.00494671899 -0.0035709357 0.000023461161 0.00527019209
## x36 0.01300331087 -0.0055125225 -0.006960077058 -0.00216270628
## x37 0.00062528635 0.0056312441 -0.001916585186 0.01081618198
## x38 -0.00532174158 -0.0096126433 -0.002612954042 -0.00740672030
## x39 -0.01519861718 -0.0060192279 -0.001590693508 0.00199191748
## x40 0.00547659518 -0.0015740593 -0.003301366782 0.00183022533
## x41 -0.00006782043 0.0091774769 -0.001011400435 -0.00443356943
## x42 -0.01459502987 0.0053190333 0.004464780174 0.00282595442
## x43 0.00304515719 0.6287787652 -0.000669749518 -0.00731509748
## x44 -0.00936882251 0.0055686637 0.007232209975 0.00161348819
## x45 -0.00256161234 0.0028087189 -0.001412855617 0.00918239592
## x46 -0.00081831598 0.0061653574 0.004559410862 -0.00960332640
## x47 0.00982322168 -0.0007783334 -0.007210768636 0.00867798029
## x48 -0.00040934829 0.0011962350 -0.000034247476 -0.00962748745
## x49 -0.00468259188 -0.0023350552 -0.010017301086 0.00290851715
## x50 0.00475574371 -0.0035628119 -0.001964184680 -0.00228153879
## x51 0.00015962439 0.0045152746 -0.000557468581 -0.00092012159
## x52 -0.00641516162 0.0041720828 0.003341829081 -0.00668492584
## x54 0.01373579360 0.0026600233 -0.012058643847 -0.00164340602
## x55 0.00392037916 -0.0083456912 0.003823197858 0.01654790543
## x56 0.00477399282 -0.0195057832 0.004264018714 -0.00575818745
## x57 -0.00098510806 -0.0102260161 0.005746202520 0.00562086954
## x58 -0.00504397928 -0.0020464932 0.002954739962 0.00444603636
## x60 0.00272898963 -0.0063567286 0.006710877849 0.00024172324
## x61 0.00280295869 -0.0023229135 0.004220987664 0.00155623174
## x63 -0.00106935519 -0.0101820020 0.005564650859 0.00572760522
## x64 0.00923673406 0.0083821744 0.004284168438 -0.00398382713
## x65 -0.00696785032 -0.0018728372 0.000025007487 0.00012968988
## x66 -0.00889809908 -0.0077704053 0.999999984791 -0.00768085868
## x68 0.00442107737 -0.0009841960 -0.000081945675 0.00593458796
## x69 -0.00569300076 0.0097366149 0.004616664052 0.00918610090
## x70 0.00148546811 -0.0047590343 0.000004387386 -0.00323034172
## x71 -0.00136916886 -0.0040613575 -0.000268851100 -0.00613476262
## x72 0.00302947159 0.0103560970 0.007703063481 0.00853233252
## x73 -0.00541339307 0.0089657570 -0.013172013956 -0.00273206746
## x74 0.00023417864 -0.0114414991 -0.003348020467 0.00168356603
## x75 0.00673731760 0.0084115813 -0.001779871863 -0.00478586039
## x76 0.00273094497 -0.0063573630 0.006709410724 0.00024083667
## x77 0.00628604770 0.0071126623 0.000513558694 0.00536362662
## x79 -0.01148044208 -0.0002598133 0.004091511886 -0.00635433158
## x80 -0.00248574640 0.0045386559 0.000322468572 -0.00401654573
## x81 -0.00091044292 0.0135205375 -0.002507245475 -0.00236130593
## x82 0.01143051864 -0.0007450709 -0.013067504106 0.00364797255
## x83 1.00000000000 -0.0030904878 -0.008899858902 -0.01115077740
## x84 -0.00309048778 1.0000000000 -0.007770305809 -0.00033308345
## x85 -0.00889985890 -0.0077703058 1.000000000000 -0.00768022330
## x86 -0.01115077740 -0.0003330834 -0.007680223300 1.00000000000
## x87 0.00127373669 -0.0028830729 0.005559013056 -0.00030986400
## x88 0.00487898839 -0.0077370069 -0.009280956564 -0.00539648540
## x89 0.00156138279 0.0063603079 0.007988469600 0.00500438060
## x90 0.00450408876 -0.0037115601 -0.002083506918 -0.00149216249
## x92 0.00664966354 0.0019159855 -0.000523677651 0.00060441836
## x93 0.01571013744 -0.0027274814 0.002741254939 -0.01332411247
## x94 -0.00657673530 0.0011038627 0.007466501636 -0.00584883984
## x95 0.00379567813 -0.0020866015 -0.004218470479 -0.00785815853
## x96 -0.00092477555 -0.0086787297 0.005435117805 0.00516543790
## x97 -0.00933462441 -0.0090895807 -0.001598833068 0.00693931594
## x98 0.00572217714 -0.0058420903 -0.000878300709 -0.01169062290
## x99 -0.00734487923 -0.0127324708 -0.003397581106 -0.00451548011
## x101 0.00243465887 0.0031845158 0.003247240706 -0.00130178074
## x102 0.00919527048 -0.0019116443 0.002492222774 -0.00876204429
## x103 0.00222932589 0.0032204512 0.001639681803 0.00114252993
## x104 -0.00079882309 0.0046747470 -0.001867562644 0.00589063970
## x105 0.00715826518 -0.0059710204 0.010662471335 -0.00204330900
## x106 0.00301823216 0.0019692885 -0.004519312890 0.00420034701
## target 0.03045251240 -0.0216697834 -0.004579574275 0.00684187485
## x87 x88 x89 x90
## x1 -0.005444648652 -0.00170080549 0.002656185504 0.00623748461
## x3 0.000967696103 -0.01433240352 0.008635813679 -0.01368948264
## x4 0.005217879829 0.00687958752 -0.006770333686 0.00760008336
## x6 0.008103697629 -0.00258353098 -0.005998693493 -0.00283078981
## x7 -0.011702512880 -0.01200488803 0.001518865425 0.01095713642
## x8 -0.005655439509 0.00632583984 0.003547063301 0.00958571027
## x9 -0.004823431356 -0.00815768421 -0.002489268481 -0.00248239481
## x10 0.000851382665 -0.00301838858 0.003140828623 -0.00156110858
## x11 0.001553773607 -0.01031403442 -0.008709175036 -0.00334986223
## x12 0.004616710935 -0.00366697447 -0.002714710027 0.00390899032
## x13 -0.008943765324 0.01803772343 0.002891698662 -0.00853386638
## x14 -0.001352053787 -0.00325962948 0.005749280624 -0.00187285765
## x15 -0.004515347223 -0.00063070205 0.003046486044 0.00524600919
## x16 0.002169914137 -0.00127739453 0.008221453436 -0.00116332576
## x17 0.001776378051 -0.00031618295 -0.001542786895 0.00290057056
## x18 0.003230232192 -0.01245856855 0.010208181367 0.00159193826
## x19 0.003731544055 -0.00729867761 -0.003202102487 0.00036042556
## x20 -0.007196059647 -0.00174585992 0.000003180418 0.00724132205
## x21 0.005036187774 -0.00028791214 -0.005912345203 -0.00916602803
## x22 -0.000187732241 0.00528061539 -0.009899330706 -0.00642709697
## x23 0.018554989783 -0.00546427193 0.001528259409 -0.00087966361
## x24 -0.001265420971 -0.00714822112 0.002074854110 -0.00265915042
## x25 -0.000498783184 -0.00812176781 -0.001707655414 -0.00376955330
## x26 0.005385015379 0.00595991808 0.001863110969 0.01091828576
## x29 -0.000653906364 -0.00744739415 0.002967103220 -0.00272578191
## x30 0.002831947308 0.00315992394 -0.007668160164 -0.01031453675
## x31 -0.002883119052 -0.00773702438 0.006360249111 -0.00371157416
## x32 0.011064425638 0.99999956902 0.013775081648 -0.00218027108
## x33 0.002074521361 -0.01037129314 0.001144840189 0.00006124064
## x34 0.000302706345 -0.01128158969 -0.007349998871 0.00252431474
## x35 -0.002214713319 -0.00086346890 0.011040407950 0.00018216794
## x36 0.013658624337 0.00079193876 -0.001359640631 0.00821465411
## x37 0.001329496069 0.00049838244 0.003812943949 0.00387119847
## x38 -0.010503571500 0.00137067906 -0.000058425206 0.00645892740
## x39 0.000212540204 -0.00103542841 0.002457134468 0.00348605644
## x40 -0.000006787911 -0.00428854331 0.003413651027 -0.00105996000
## x41 0.009035004593 -0.00005206408 0.010787922311 0.00180377542
## x42 -0.002769096876 0.00045185125 -0.000590389483 0.00504408033
## x43 0.000657055009 -0.00755152520 0.004589573903 0.00358694563
## x44 0.008351123693 -0.00143245482 0.011629312736 -0.00285733461
## x45 -0.010909472882 0.00036803280 -0.002261404388 -0.00531475335
## x46 0.003668407589 -0.00637589826 -0.013318802481 -0.00642701190
## x47 0.004716233152 -0.00009276725 0.005374589358 0.01071645051
## x48 -0.000938047302 0.00324845619 0.005441511588 -0.00484926495
## x49 0.004888520215 -0.00289502422 -0.002261871733 -0.00526584414
## x50 0.012628050770 -0.00226436671 -0.006131786026 0.99852498831
## x51 0.003480235976 -0.00551270742 -0.002536605611 0.00745096347
## x52 0.002666311560 -0.00372250672 -0.003539588978 -0.00919321599
## x54 0.003920419922 0.00141989186 -0.011799677257 -0.00188106519
## x55 0.004899497001 0.00617828472 -0.001628819302 -0.01040666176
## x56 -0.002646944424 0.00058886435 0.005772470496 0.00068894189
## x57 -0.000918644105 -0.00430348822 0.006457828962 0.00564636611
## x58 -0.000361641614 0.00455861493 0.010139273041 0.00159257170
## x60 0.007037199046 -0.00223636503 -0.005728121685 -0.00176607127
## x61 -0.001223685845 0.00673978532 0.000036754895 0.01113561586
## x63 -0.001004292865 -0.00448134582 0.006598556595 0.00551736499
## x64 -0.000493825873 -0.00735809947 0.002801338300 -0.00254178376
## x65 0.006041417006 0.00404391431 -0.002673561352 0.00187531947
## x66 0.005559365320 -0.00928165071 0.007986139389 -0.00208447571
## x68 0.002782307902 -0.00172642661 -0.003828258314 0.00645557803
## x69 -0.005362600385 -0.00455467993 -0.003021281193 0.00177360295
## x70 -0.000549042552 -0.00558628879 -0.000729429002 -0.00083576928
## x71 0.007802027792 0.00429605661 0.000766056911 -0.00778356693
## x72 0.001050754672 -0.00085436335 -0.006503064363 0.00128709978
## x73 0.001697956464 0.00019892018 -0.006877431140 -0.00880661118
## x74 -0.007948462059 -0.00011986323 -0.002216137893 -0.00211409964
## x75 -0.007570362417 0.01207437378 -0.001074017351 -0.00342891143
## x76 0.007037623338 -0.00223459517 -0.005728144591 -0.00176618908
## x77 -0.000749605674 -0.00102947346 0.009430468128 -0.00099823965
## x79 0.004460925051 0.00402396710 0.005966853811 0.00166278706
## x80 -0.008024107268 0.00199126584 0.005501245567 -0.01024160237
## x81 -0.016526513423 -0.00221168506 0.001610009480 -0.01417548473
## x82 -0.005274348165 0.00178216833 0.001700603202 -0.00182281454
## x83 0.001273736692 0.00487898839 0.001561382793 0.00450408876
## x84 -0.002883072870 -0.00773700693 0.006360307926 -0.00371156011
## x85 0.005559013056 -0.00928095656 0.007988469600 -0.00208350692
## x86 -0.000309864001 -0.00539648540 0.005004380604 -0.00149216249
## x87 1.000000000000 0.01106908811 0.011291371816 0.01278759098
## x88 0.011069088115 1.00000000000 0.013777456224 -0.00217024162
## x89 0.011291371816 0.01377745622 1.000000000000 -0.00548564048
## x90 0.012787590985 -0.00217024162 -0.005485640476 1.00000000000
## x92 0.000249677866 0.00515704893 -0.009658377392 -0.00653577516
## x93 0.009870972185 0.00878820618 0.005528390724 0.00755157907
## x94 0.010545791208 0.00862842622 0.010482021376 -0.00928870345
## x95 -0.006120752243 0.00207485575 -0.002370395428 0.00151824104
## x96 0.000045207829 -0.00563269202 0.005573373645 0.00745942749
## x97 0.010103295596 0.00669285018 0.002385637533 0.00384119363
## x98 0.010430631669 -0.00907904761 -0.001424285760 -0.00687584791
## x99 -0.004453283996 -0.00411886794 -0.006354052468 -0.00283043988
## x101 -0.007197072586 -0.00174110244 -0.000003921547 0.00724042159
## x102 0.001766476133 0.00079090491 -0.005101478994 -0.00325168522
## x103 -0.011659907939 -0.00956719485 0.007860688269 -0.00875499968
## x104 0.016774299030 0.00909065857 -0.002525830567 0.01274416451
## x105 0.000765268784 -0.01276661624 0.010443662728 0.00014209051
## x106 0.002937076638 -0.00494709651 0.000888806397 -0.00634189487
## target -0.084716273236 -0.01403683433 -0.006999926695 -0.08754107733
## x92 x93 x94 x95 x96
## x1 -0.00575664741 0.0018367363 -0.0071169177 -0.00933568431 -0.00893078450
## x3 0.00593446943 -0.0027965355 0.0115560370 0.01074856491 0.00255692849
## x4 -0.00745757803 -0.0085451509 0.0010126975 0.00388342212 0.00366649667
## x6 -0.00405367108 -0.0052441338 0.0050227977 -0.00177863205 0.00267579118
## x7 0.00416348592 -0.0013624711 0.0124609783 -0.00578059447 0.00690966011
## x8 0.00681134606 -0.0049739999 -0.0054842873 0.00506795557 0.00506685439
## x9 0.00762042544 -0.0115958220 -0.0094313673 -0.00402464465 0.00200355150
## x10 -0.00082579627 -0.0018052261 -0.0114525232 -0.01069671908 0.00231425106
## x11 0.01382444638 -0.0026728292 0.0033347320 -0.00511968512 0.00101074598
## x12 -0.00154864317 0.0017274304 -0.0056126306 -0.00286028543 0.00521907609
## x13 -0.00025690679 0.0101606194 -0.0025890243 -0.00078408672 -0.01166976043
## x14 -0.00008627035 -0.0124947673 -0.0034329996 -0.00463494484 0.00585779005
## x15 0.01028986474 0.0055528379 -0.0005833262 0.00383067058 0.00576172410
## x16 0.00338412090 -0.0065568139 0.0067168623 -0.00284372919 0.00304922788
## x17 0.00626905669 -0.0049176965 0.0001539524 0.00365497290 0.00047240136
## x18 -0.01174909514 -0.0000680892 -0.0031578495 0.00126109777 -0.00299083893
## x19 -0.00344119388 -0.0018451017 0.0050308023 0.00119992362 0.01138228954
## x20 -0.00481738438 0.0075398744 0.0031112847 -0.00872892354 -0.00449624456
## x21 0.01475599194 0.0030434520 -0.0043727232 -0.00622777919 -0.00023498927
## x22 0.99963861574 0.0040221651 -0.0033499798 0.00494543985 -0.00083289944
## x23 0.00547083849 -0.0010771591 -0.0029234940 -0.00502169282 -0.00558912757
## x24 0.00042415052 0.0027387915 -0.0039031482 0.00489735558 0.00127697538
## x25 -0.00683657426 -0.0008986101 -0.0003887972 0.00169567727 0.00370618600
## x26 0.00191705406 0.0087629992 -0.0028904008 0.00973988617 0.00514761580
## x29 -0.00025074572 0.0041900103 -0.0043212310 0.00468765418 0.00019846780
## x30 0.00363320546 -0.0005532602 -0.0023570691 -0.00236549835 0.00527909623
## x31 0.00191595943 -0.0027275895 0.0011038414 -0.00208671224 -0.00867865886
## x32 0.00515492439 0.0087804838 0.0086301455 0.00206444845 -0.00563729367
## x33 0.00023239384 0.0094434213 0.0070853045 -0.01615613520 -0.00494712484
## x34 -0.00964937767 -0.0008597285 -0.0062194707 0.00323768883 0.00518822369
## x35 0.00452358840 0.0109208513 -0.0060868134 0.01285585933 0.00286721336
## x36 -0.00130574403 0.0019633256 0.0056346263 -0.00187365410 -0.00765219362
## x37 0.00424220214 0.0014329454 -0.0019955040 0.00162621810 0.00600847522
## x38 0.01065342171 -0.0020505691 -0.0072775781 0.00026372436 0.00233525429
## x39 0.00483076963 0.0027073284 0.0047335447 0.00493307626 -0.00580979189
## x40 -0.01018884254 -0.0059241253 0.0093971230 0.00787571420 0.00305299127
## x41 -0.00365360606 -0.0149781653 -0.0062433472 0.01191536570 -0.00324276017
## x42 0.00174380380 0.0060518399 -0.0022462502 -0.00430711648 -0.00008491819
## x43 0.00354678526 -0.0065575914 0.0080838735 0.00475538457 -0.00050756095
## x44 0.00273899843 -0.0160191921 0.0111723515 -0.00038884619 0.00256201928
## x45 0.00421827011 0.0002024476 0.0006898639 0.00081884671 -0.01178851906
## x46 -0.00732316118 -0.0016409937 -0.0113708279 0.00532295232 -0.00091662535
## x47 0.00730669740 0.0058120918 -0.0161701087 -0.01535829716 -0.00013179740
## x48 0.00129219204 -0.0043309463 0.0010982107 -0.00584429471 -0.00439836324
## x49 0.00496935152 0.0019311944 -0.0085528822 0.00000828874 0.00101011141
## x50 -0.00645170628 0.0076588229 -0.0090652502 0.00157608368 0.00748139696
## x51 -0.00009412048 -0.0019100312 0.0168221420 -0.01093796251 0.26085778101
## x52 -0.00069368886 0.0028754830 -0.0102782061 0.00383139882 -0.00381906259
## x54 -0.00176793173 0.0044499722 -0.0056286463 0.00307017200 0.01028953904
## x55 -0.01000951409 -0.0074599133 -0.0088061679 0.00501125086 0.00132937194
## x56 -0.00310447615 0.0003850924 -0.0047807807 0.00121735617 0.00533298430
## x57 -0.00093703327 -0.0087505582 0.0114970622 -0.00126884739 0.96380693881
## x58 -0.00513694342 -0.0044074709 0.0029614725 0.00296623853 0.00184078674
## x60 -0.00388902981 -0.0046904300 0.0048097460 -0.00022258376 0.00227170078
## x61 -0.00882999391 0.0043529416 0.0011110465 0.00375963101 0.00324268257
## x63 -0.00099183741 -0.0087316072 0.0115254376 -0.00126792611 0.96365042047
## x64 0.00003258859 0.0041039457 -0.0042632485 0.00481740289 0.00014675290
## x65 0.00470235219 -0.0020466979 -0.0007737884 0.00365108472 0.00370974870
## x66 -0.00052496727 0.0027419195 0.0074672901 -0.00421874417 0.00543447738
## x68 0.00939811217 0.0008878495 0.0082074813 -0.00395690534 -0.00607548998
## x69 0.00766408050 -0.0071416554 -0.0043941285 0.01074265929 -0.00187663823
## x70 -0.00028660448 0.0021116865 0.0032378730 0.00078260554 -0.00119478121
## x71 0.00594986475 0.0024047534 -0.0054370736 0.00097404901 0.00502824231
## x72 -0.00118396614 -0.0023253303 0.0031381445 -0.00165609985 -0.00613113754
## x73 -0.00133780374 0.0045794039 0.0035105714 0.01294186191 -0.00806401347
## x74 0.00003180002 0.0050965740 -0.0086365082 0.00791840775 0.00463959124
## x75 0.00606569944 0.0042259610 0.0049161305 -0.00004156852 -0.00650831013
## x76 -0.00388832892 -0.0046914633 0.0048090500 -0.00021998070 0.00226769303
## x77 0.00319598649 0.0093876063 0.0074560354 -0.00760807181 -0.00025242627
## x79 0.00303404070 0.0027140687 -0.0148605591 0.00266807842 0.00309059088
## x80 0.00439050466 -0.0018512399 -0.0046461499 -0.00796358432 -0.00674314091
## x81 -0.00547529748 0.0081735406 -0.0059777170 0.00849615903 0.00475184546
## x82 -0.00899813781 -0.0020817904 0.0041270022 -0.00648723075 -0.01114899913
## x83 0.00664966354 0.0157101374 -0.0065767353 0.00379567813 -0.00092477555
## x84 0.00191598553 -0.0027274814 0.0011038627 -0.00208660152 -0.00867872967
## x85 -0.00052367765 0.0027412549 0.0074665016 -0.00421847048 0.00543511780
## x86 0.00060441836 -0.0133241125 -0.0058488398 -0.00785815853 0.00516543790
## x87 0.00024967787 0.0098709722 0.0105457912 -0.00612075224 0.00004520783
## x88 0.00515704893 0.0087882062 0.0086284262 0.00207485575 -0.00563269202
## x89 -0.00965837739 0.0055283907 0.0104820214 -0.00237039543 0.00557337365
## x90 -0.00653577516 0.0075515791 -0.0092887035 0.00151824104 0.00745942749
## x92 1.00000000000 0.0039857391 -0.0034806790 0.00483723246 -0.00091084267
## x93 0.00398573909 1.0000000000 0.0054197743 -0.00181096015 -0.00895665616
## x94 -0.00348067902 0.0054197743 1.0000000000 -0.00437681662 0.01559434547
## x95 0.00483723246 -0.0018109601 -0.0043768166 1.00000000000 -0.00415983129
## x96 -0.00091084267 -0.0089566562 0.0155943455 -0.00415983129 1.00000000000
## x97 -0.01277278331 -0.0065892239 -0.0001291425 0.00003724198 0.00922486761
## x98 -0.00068744989 -0.0078384628 -0.0137402924 -0.00507630182 -0.00578629261
## x99 0.00781594149 -0.0069489026 0.0085838384 -0.00583514284 -0.01393642225
## x101 -0.00482111111 0.0075471432 0.0031129304 -0.00872955256 -0.00449246795
## x102 -0.01143506632 0.0096093314 0.0040542157 -0.00146149257 0.00039463253
## x103 0.00496914007 -0.0136187251 0.0056944537 -0.00885155569 0.00365825434
## x104 0.01217828716 0.0125954251 0.0032104326 -0.00656205721 0.00447972366
## x105 -0.01070836711 0.0003708618 -0.0061978896 0.00153488214 -0.00320899176
## x106 -0.01530240273 0.0009907151 -0.0050839198 -0.00282961525 -0.00398442741
## target 0.01156129594 -0.0126076439 0.1496535008 -0.06037351650 0.14865637875
## x97 x98 x99 x101
## x1 0.01489301012 0.00115194397 0.0094124248 0.005747032799
## x3 -0.00086653066 -0.00132830396 -0.0048899289 0.002590851001
## x4 0.00054274534 -0.00533495149 -0.0026542468 0.001120647258
## x6 -0.00375402551 0.00223294440 -0.0087783851 -0.006658600712
## x7 -0.01395602574 0.00017105325 0.0032410882 -0.001747026451
## x8 -0.00124724451 0.00487826846 0.0049957200 0.002807668687
## x9 -0.00128674537 0.00099216615 0.0008360126 0.000587295048
## x10 0.01062801188 -0.00208354998 -0.0090422522 0.015819074253
## x11 0.00655859018 -0.00332476158 0.0018170323 -0.001151880775
## x12 -0.00129003055 -0.00144106550 0.0002281127 -0.006777517815
## x13 -0.00101418481 -0.00264138420 -0.0045149419 -0.002268388703
## x14 0.00707094318 -0.01139515974 -0.0050989997 -0.002913787996
## x15 0.01063876773 -0.00685797848 -0.0066236411 0.000279764225
## x16 -0.00073697351 0.01268090954 0.0025968122 0.003998629028
## x17 -0.00375012548 0.00141785183 0.0085037645 0.002578758796
## x18 0.00646966909 -0.00532025602 -0.0013423481 -0.005467996615
## x19 0.00565546703 -0.01055252446 -0.0028003802 0.004227377861
## x20 0.00749822113 0.00206235539 0.0012440691 0.999998798033
## x21 -0.00554149781 -0.00852181405 0.0004771070 0.001626190539
## x22 -0.01278304838 -0.00072809076 0.0076623347 -0.004737648144
## x23 -0.00127065233 0.00568105913 -0.0051126857 -0.005949714554
## x24 -0.00709282172 -0.00163225161 0.0032757419 0.007458074236
## x25 -0.00166361336 -0.00268089319 0.0102284535 -0.004601785665
## x26 -0.00844184499 0.00478162216 -0.0100375360 0.001163645974
## x29 -0.00564219152 -0.00243142760 0.0036068432 0.005419591955
## x30 0.00975038425 -0.00024892774 -0.0126997885 0.003537369684
## x31 -0.00908970060 -0.00584216230 -0.0127325584 0.003184432176
## x32 0.00670049378 -0.00908354659 -0.0041110082 -0.001739542976
## x33 -0.00967613868 0.00377989183 0.0013715513 0.005248309342
## x34 0.00616064483 0.00517252911 0.0048589880 -0.000934412359
## x35 0.00077819831 0.01091848619 -0.0079138696 -0.003859308898
## x36 -0.00057061659 -0.01063326038 -0.0009733391 -0.000341473106
## x37 0.00533733063 -0.01137617607 -0.0042494605 -0.005470623499
## x38 0.00445312398 -0.00186892067 -0.0054353436 0.009181721906
## x39 -0.00267533637 -0.00009439528 -0.0027682840 0.002527963166
## x40 -0.00874524830 0.00055010243 -0.0042115380 0.003095835475
## x41 -0.00626134827 -0.00693419261 0.0014616233 0.006746568296
## x42 0.00219676665 0.00376007405 -0.0041666019 0.009460129853
## x43 0.00024844924 -0.01175225340 -0.0003684985 0.008617429934
## x44 0.00607143171 -0.00414659869 -0.0090636857 0.005046178352
## x45 -0.00577861732 0.01092719314 0.0010754710 0.006508565028
## x46 0.00618243941 -0.00500755822 -0.0143988326 -0.002653394097
## x47 -0.00401580945 -0.00407921191 -0.0007264592 -0.004151224661
## x48 0.00260364397 0.00573344647 -0.0031582899 0.001073825360
## x49 0.00031854295 -0.00174622965 -0.0077790831 0.004428720028
## x50 0.00402006405 -0.00673059061 -0.0029347619 0.007768767691
## x51 0.00073964745 0.00940842321 0.0051634910 -0.010047840581
## x52 -0.00145671062 0.00037587992 -0.0159857236 0.002268079101
## x54 -0.00542982663 -0.00068775499 0.0005413487 0.015885995669
## x55 -0.01201732986 0.00285024549 -0.0032422177 0.012060522507
## x56 0.00503950198 0.00678514563 -0.0052789864 0.004227882604
## x57 0.00934853855 -0.00860577743 -0.0158730286 -0.001886694205
## x58 -0.00646886216 0.00302108037 0.0060317357 0.008377709808
## x60 -0.00381810498 0.00200483461 -0.0090583007 -0.006811684680
## x61 -0.00620215309 -0.00359110415 -0.0045464243 0.004497185768
## x63 0.00946129114 -0.00860584560 -0.0158583998 -0.001871297479
## x64 -0.00576687539 -0.00240904520 0.0035214497 0.005670355408
## x65 -0.01267740941 -0.00304388290 -0.0018162668 0.000010817109
## x66 -0.00159910482 -0.00087738955 -0.0033974022 0.003248184086
## x68 -0.00403860292 -0.00212276248 -0.0080393693 0.006850376885
## x69 -0.00367379902 -0.00725089437 0.0012941242 0.003222879838
## x70 -0.00006888833 -0.00675580187 0.0066294512 0.005519566716
## x71 0.00134629416 0.00339479876 -0.0128409668 0.000119329422
## x72 0.00652977091 0.00673608697 0.0044172544 -0.014669613502
## x73 0.00830450526 -0.00067909341 -0.0069294815 0.005848018638
## x74 0.00027792651 -0.00512399651 -0.0105007642 0.007088638849
## x75 -0.00395545357 0.00116227467 0.0129548171 0.115240393600
## x76 -0.00381858619 0.00200410005 -0.0090571508 -0.006812242470
## x77 0.00043126563 -0.00485451539 0.0049967445 0.000217341474
## x79 0.00001251808 -0.01121613943 0.0147626526 0.001239955499
## x80 0.00361842810 0.00370273493 -0.0030306315 -0.002422941859
## x81 0.00662548667 -0.00063093867 -0.0038736579 -0.002265942070
## x82 -0.01447458206 -0.00101052579 -0.0088354329 -0.001429512518
## x83 -0.00933462441 0.00572217714 -0.0073448792 0.002434658872
## x84 -0.00908958069 -0.00584209030 -0.0127324708 0.003184515795
## x85 -0.00159883307 -0.00087830071 -0.0033975811 0.003247240706
## x86 0.00693931594 -0.01169062290 -0.0045154801 -0.001301780743
## x87 0.01010329560 0.01043063167 -0.0044532840 -0.007197072586
## x88 0.00669285018 -0.00907904761 -0.0041188679 -0.001741102438
## x89 0.00238563753 -0.00142428576 -0.0063540525 -0.000003921547
## x90 0.00384119363 -0.00687584791 -0.0028304399 0.007240421594
## x92 -0.01277278331 -0.00068744989 0.0078159415 -0.004821111112
## x93 -0.00658922391 -0.00783846281 -0.0069489026 0.007547143230
## x94 -0.00012914251 -0.01374029243 0.0085838384 0.003112930371
## x95 0.00003724198 -0.00507630182 -0.0058351428 -0.008729552558
## x96 0.00922486761 -0.00578629261 -0.0139364223 -0.004492467955
## x97 1.00000000000 -0.00173416085 0.0063533887 0.007516767043
## x98 -0.00173416085 1.00000000000 -0.0032263448 0.002068143187
## x99 0.00635338869 -0.00322634481 1.0000000000 0.001263011335
## x101 0.00751676704 0.00206814319 0.0012630113 1.000000000000
## x102 0.00624003798 -0.01103343097 -0.0002664602 -0.004232272625
## x103 0.01262285588 -0.00345719344 0.0047682568 -0.002985764976
## x104 0.00519705077 0.00754987429 -0.0008136975 -0.004298165952
## x105 0.00854524155 -0.00299783344 -0.0048838396 -0.005486824171
## x106 -0.00138256804 -0.00501923313 -0.0098475698 -0.001312024258
## target -0.00155234542 0.05008251378 0.0197798497 -0.215846998896
## x102 x103 x104 x105
## x1 0.0052599698 0.00843292525 -0.00064249855 0.00287236485
## x3 -0.0004619518 0.01012124310 -0.01144795408 0.00465596902
## x4 0.0111674075 -0.00017890514 0.00880994222 0.00595745474
## x6 -0.0066419905 0.00384052811 0.00264747022 -0.00284199294
## x7 0.0103721065 0.00933002144 0.00066732139 0.00861891416
## x8 -0.0037147151 0.00369962539 -0.00120108073 0.00173046886
## x9 0.0019290065 -0.00585335083 0.00145158579 -0.00511673657
## x10 0.0027833234 0.00687168756 0.00285635519 -0.00009442238
## x11 0.0064917045 0.00545738126 0.01011802873 0.00623340299
## x12 0.0071266702 0.00008436634 -0.00486341629 0.00214848911
## x13 0.0030582782 0.01686185583 -0.00989126855 -0.00228853719
## x14 -0.0077178158 0.00276955478 0.00679507755 -0.00291321011
## x15 -0.0068059873 0.00494295355 0.00592425437 0.00488194069
## x16 -0.0041749905 0.00741916587 0.00369132847 0.00165636145
## x17 -0.0007741654 0.00743608030 0.00119721554 0.00884593796
## x18 -0.0146862741 -0.00954307962 0.00058741845 0.98004156724
## x19 0.0050369477 -0.00084100432 0.00507471601 0.00071720764
## x20 -0.0042349695 -0.00298536695 -0.00428875627 -0.00550626324
## x21 0.0026417041 0.00564766229 0.00178360038 0.00112232705
## x22 -0.0116068167 0.00520014352 0.01217573244 -0.01078186241
## x23 -0.0137414347 -0.00091407075 0.00485808198 0.00647480584
## x24 -0.0102708516 -0.00886184731 -0.00352094916 -0.00343502164
## x25 0.0010972586 -0.00065124250 0.01214011225 -0.00223673004
## x26 0.0105345183 0.00497296460 0.00090779687 0.00428601302
## x29 -0.0100189508 -0.00908589174 -0.00350189928 -0.00500104820
## x30 -0.0068388931 -0.00536621872 -0.01025750303 -0.00221584897
## x31 -0.0019116434 0.00322042879 0.00467474336 -0.00597099485
## x32 0.0007788845 -0.00957301183 0.00908902463 -0.01277011780
## x33 -0.0030352578 0.00053062822 0.00660148041 0.00511068693
## x34 -0.0133189296 0.00775767302 -0.00083399127 0.00896236760
## x35 -0.0024442821 0.00562006666 0.00004279721 0.00539359210
## x36 -0.0014031833 0.00067735555 -0.00013909165 0.00257974350
## x37 0.0009093188 -0.00292491443 0.00069996996 0.00558617087
## x38 -0.0015415517 0.00488165554 -0.01357176407 -0.01777770915
## x39 0.0042337462 -0.00019627102 0.00406350533 -0.01177009259
## x40 0.0026512348 -0.00058897454 0.00408626318 -0.00024853547
## x41 0.0034615324 0.00382102687 0.00408363034 0.00087705359
## x42 0.0023976603 -0.00384302716 -0.00945826325 -0.00298329657
## x43 -0.0047074981 0.00427055373 -0.00238415840 -0.01392085220
## x44 0.0063369006 0.00426054093 -0.00006066473 -0.00242442519
## x45 -0.0016191381 -0.00455622188 0.00578880877 0.00092179070
## x46 0.0007848726 0.00278699253 -0.00280838594 -0.00608693847
## x47 -0.0017416254 0.01178587842 0.01127799860 -0.01112038313
## x48 -0.0023275012 -0.00648512729 0.00109336139 0.00531007538
## x49 0.0131001481 0.00708933104 0.00746819551 -0.00310217256
## x50 -0.0029721948 -0.00828474737 0.01272877795 0.00027196178
## x51 0.0049229006 -0.00566657102 -0.00240811312 0.00379995441
## x52 -0.0070108700 0.00116792343 -0.00165707270 0.00265279616
## x54 0.0014573461 -0.00910906528 -0.00485075748 -0.00224653482
## x55 0.0008663793 -0.00307530677 -0.00628856867 -0.00236398714
## x56 0.0017987153 -0.00643628489 0.00584815919 0.00969426392
## x57 -0.0009238875 0.00538542887 0.00529402860 -0.00434768494
## x58 -0.0074993026 -0.00468567715 -0.00654520874 0.00096037864
## x60 -0.0069752349 0.00409250645 0.00296672699 -0.00338285415
## x61 0.0006579387 0.00358322052 0.00884366270 -0.00073015624
## x63 -0.0009306133 0.00542430796 0.00529757688 -0.00440027312
## x64 -0.0101372274 -0.00901129374 -0.00346431003 -0.00478580304
## x65 -0.0070178262 0.00643910602 0.00269349288 -0.00548046393
## x66 0.0024911365 0.00163923180 -0.00186862116 0.01066093943
## x68 -0.0009789940 -0.01186673571 -0.00112357406 0.00491819950
## x69 0.0054989194 -0.00828450347 -0.00025897284 -0.00620553871
## x70 -0.0015086437 0.00264640754 -0.00014973267 0.00377358216
## x71 0.0029214851 -0.00273735801 0.00159524212 0.01329256567
## x72 -0.0054960170 -0.00811428741 0.00222521254 0.00580264588
## x73 -0.0004996214 -0.00688644978 0.01399986464 0.00574096955
## x74 -0.0006724203 0.00065331686 -0.00793059828 -0.00927725635
## x75 0.0041911943 0.00155118005 -0.00498403569 0.00945014645
## x76 -0.0069763579 0.00409311513 0.00296812509 -0.00338057390
## x77 -0.0051832614 -0.00356268644 -0.00004695381 -0.00523820208
## x79 0.0071436855 0.00231697755 0.00329283084 0.00601265128
## x80 0.0003184470 -0.00686094559 -0.00161846987 -0.00540319967
## x81 0.0102523202 -0.00541639298 -0.00168938848 -0.00684263216
## x82 -0.0060398871 -0.00057593167 -0.00586553605 -0.00165644735
## x83 0.0091952705 0.00222932589 -0.00079882309 0.00715826518
## x84 -0.0019116443 0.00322045116 0.00467474701 -0.00597102036
## x85 0.0024922228 0.00163968180 -0.00186756264 0.01066247134
## x86 -0.0087620443 0.00114252993 0.00589063970 -0.00204330900
## x87 0.0017664761 -0.01165990794 0.01677429903 0.00076526878
## x88 0.0007909049 -0.00956719485 0.00909065857 -0.01276661624
## x89 -0.0051014790 0.00786068827 -0.00252583057 0.01044366273
## x90 -0.0032516852 -0.00875499968 0.01274416451 0.00014209051
## x92 -0.0114350663 0.00496914007 0.01217828716 -0.01070836711
## x93 0.0096093314 -0.01361872506 0.01259542505 0.00037086175
## x94 0.0040542157 0.00569445375 0.00321043262 -0.00619788962
## x95 -0.0014614926 -0.00885155569 -0.00656205721 0.00153488214
## x96 0.0003946325 0.00365825434 0.00447972366 -0.00320899176
## x97 0.0062400380 0.01262285588 0.00519705077 0.00854524155
## x98 -0.0110334310 -0.00345719344 0.00754987429 -0.00299783344
## x99 -0.0002664602 0.00476825677 -0.00081369754 -0.00488383956
## x101 -0.0042322726 -0.00298576498 -0.00429816595 -0.00548682417
## x102 1.0000000000 0.00198511364 0.00082714800 -0.01274576492
## x103 0.0019851136 1.00000000000 0.00033544595 -0.01030007101
## x104 0.0008271480 0.00033544595 1.00000000000 0.00230462538
## x105 -0.0127457649 -0.01030007101 0.00230462538 1.00000000000
## x106 0.0023346837 0.00564668277 0.00188557348 0.00863496498
## target -0.0062990745 0.00604773758 -0.02039293048 0.14375560494
## x106 target
## x1 -0.00446894541 -0.0270287199
## x3 0.00507840947 0.0034402204
## x4 0.00579890167 -0.0135373203
## x6 -0.00165110805 -0.0048929133
## x7 -0.00705662405 0.0379737970
## x8 -0.00863882378 0.0042591638
## x9 -0.00251378112 -0.0008952024
## x10 0.00388709211 -0.0047327872
## x11 -0.00226517678 0.0228667023
## x12 -0.00802170113 0.0050271738
## x13 -0.00089645880 -0.0671542939
## x14 0.00485228704 0.0079044581
## x15 -0.00171070874 -0.0233818108
## x16 -0.00179316192 0.0146423138
## x17 0.00437702984 -0.0044565638
## x18 0.00891377051 0.1452504090
## x19 -0.00031083369 0.0122453501
## x20 -0.00132690364 -0.2158846790
## x21 0.00117637608 -0.0125751613
## x22 -0.01531089164 0.0116775920
## x23 0.00882155457 -0.0069884525
## x24 -0.01013424102 -0.0330379323
## x25 0.00466985413 -0.0738470404
## x26 0.00170301773 0.0075339702
## x29 -0.01091286827 -0.0328878361
## x30 -0.00681771306 -0.0049996440
## x31 0.00196924377 -0.0216696208
## x32 -0.00494963155 -0.0140446478
## x33 -0.00546241633 0.0020925224
## x34 -0.00639705076 0.0148289084
## x35 -0.00020613179 0.0020529516
## x36 -0.00164548477 0.0079232026
## x37 -0.00853909218 0.0015418501
## x38 -0.00001037273 -0.0203767747
## x39 0.00249033082 0.1144497793
## x40 0.00563895986 0.0585004092
## x41 -0.00663427243 0.0195561265
## x42 0.00984679052 -0.0147733291
## x43 -0.00398788927 -0.0162713254
## x44 -0.01699722025 0.0204834239
## x45 -0.00677767907 -0.1346590433
## x46 -0.00362092346 -0.0021929399
## x47 0.00314375494 0.0004870435
## x48 0.01542917198 -0.0036338248
## x49 -0.00358382174 -0.0062700731
## x50 -0.00595295108 -0.0873657660
## x51 -0.00524274793 0.0078988384
## x52 -0.00488209606 -0.0024244373
## x54 0.00512582340 0.0488748423
## x55 0.00054810891 -0.0132194207
## x56 -0.00667238282 0.0372979341
## x57 -0.00268119634 0.1517785960
## x58 -0.00033040974 -0.0774463206
## x60 -0.00269404769 -0.0054944635
## x61 0.01836990339 0.0642024268
## x63 -0.00259166899 0.1518012735
## x64 -0.01084570432 -0.0329409920
## x65 -0.00958090094 0.0216383924
## x66 -0.00452128182 -0.0045793595
## x68 -0.00011665586 0.0036779387
## x69 0.01318885878 0.0339392631
## x70 -0.00403141585 -0.0048572077
## x71 -0.00116333554 0.0005489342
## x72 -0.00658826979 0.0118843544
## x73 0.00214176342 0.0031801763
## x74 0.00027315884 -0.0172047442
## x75 -0.00050953875 -0.1559728360
## x76 -0.00269266602 -0.0054959164
## x77 0.00038506637 -0.0021574217
## x79 -0.00388149663 -0.0019670483
## x80 -0.00277732769 0.0029682786
## x81 0.00126074342 0.0167311137
## x82 -0.00413583597 -0.1051597379
## x83 0.00301823216 0.0304525124
## x84 0.00196928851 -0.0216697834
## x85 -0.00451931289 -0.0045795743
## x86 0.00420034701 0.0068418749
## x87 0.00293707664 -0.0847162732
## x88 -0.00494709651 -0.0140368343
## x89 0.00088880640 -0.0069999267
## x90 -0.00634189487 -0.0875410773
## x92 -0.01530240273 0.0115612959
## x93 0.00099071507 -0.0126076439
## x94 -0.00508391982 0.1496535008
## x95 -0.00282961525 -0.0603735165
## x96 -0.00398442741 0.1486563788
## x97 -0.00138256804 -0.0015523454
## x98 -0.00501923313 0.0500825138
## x99 -0.00984756976 0.0197798497
## x101 -0.00131202426 -0.2158469989
## x102 0.00233468366 -0.0062990745
## x103 0.00564668277 0.0060477376
## x104 0.00188557348 -0.0203929305
## x105 0.00863496498 0.1437556049
## x106 1.00000000000 0.0148539152
## target 0.01485391518 1.00000000002º passo - Filtrar as top 10 pegando os coeficientes de correlação entre as variaveis preditoras e a variável target
# Pegando os coeficientes de correlação para a variável target
correlacao_com_target <- correlacao[,"target"]
# Removendo a correlação da variável target com ela mesma
correlacao_com_target <- correlacao_com_target[-which(names(correlacao_com_target) == "target")]
# Ordenando em valor absoluto
ordenado <- sort(abs(correlacao_com_target), decreasing = TRUE)
# Selecionando as top 10
top_10 <- ordenado[1:10]
top_10## x20 x101 x75 x63 x57 x94 x96 x18
## 0.2158847 0.2158470 0.1559728 0.1518013 0.1517786 0.1496535 0.1486564 0.1452504
## x105 x45
## 0.1437556 0.13465903º passo - Fazer a analise bivariada das variáveis quantitativas
# Histogramas para x1 e x3
hist(df$x20, main="Histograma de x20", xlab="x20")
hist(df$x101, main="Histograma de x101", xlab="x101")
hist(df$x75, main="Histograma de x75", xlab="x75")
hist(df$x63, main="Histograma de x63", xlab="x63")
hist(df$x57, main="Histograma de x57", xlab="x57")
hist(df$x94, main="Histograma de x94", xlab="x94")
hist(df$x96, main="Histograma de x96", xlab="x96")
hist(df$x18, main="Histograma de x18", xlab="x18")
hist(df$x105, main="Histograma de x105", xlab="x105")
hist(df$x45, main="Histograma de x45", xlab="x45")
# Gráficos de dispersão de x1 e x3 em relação à variável target
plot(df$x20, df$target, main="x20 vs Target", xlab="x20", ylab="Target")
plot(df$x101, df$target, main="x101 vs Target", xlab="x101", ylab="Target")
plot(df$x75, df$target, main="x75 vs Target", xlab="x75", ylab="Target")
plot(df$x63, df$target, main="x63 vs Target", xlab="x63", ylab="Target")
plot(df$x57, df$target, main="x57 vs Target", xlab="x57", ylab="Target")
plot(df$x94, df$target, main="x94 vs Target", xlab="x94", ylab="Target")
plot(df$x96, df$target, main="x96 vs Target", xlab="x96", ylab="Target")
plot(df$x18, df$target, main="x18 vs Target", xlab="x18", ylab="Target")
plot(df$x105, df$target, main="x105 vs Target", xlab="x105", ylab="Target")
plot(df$x45, df$target, main="x45 vs Target", xlab="x45", ylab="Target")
9ª etapa: Construção do modelo preditivo.
Variaveis quantitativas
Transformando as variáveis preditoras quantitativas em qualitativas. Nesta função utilizamos o método do Intervalo Interquartil (IQR), todas as colunas que apresentaram outliers são convertidas para qualitativas. Apos a convesão criamos intervalos para cada uma delas, e o número de bins é definido com base na fórmula de Sturges.
# Função para detectar se uma coluna tem outliers
detect_outliers <- function(column) {
Q1 <- quantile(column, 0.25)
Q3 <- quantile(column, 0.75)
IQR <- Q3 - Q1
lower_bound <- Q1 - 1.5 * IQR
upper_bound <- Q3 + 1.5 * IQR
return(any(column < lower_bound | column > upper_bound))
}
# Função para transformar uma coluna numérica em categorias
transform_to_categories <- function(column) {
n <- length(column)
k <- round(1 + 3.322 * log10(n)) # número de bins com base na fórmula de Sturges
return(cut(column, breaks = k, labels = FALSE))
}Aplicando a função para todos os dados quantitativos
# dadosQuant1 = dadosQuant
# Processando cada coluna do dataset
for (col_name in names(dadosQuant)) {
if (is.numeric(dadosQuant[[col_name]])) {
if (detect_outliers(dadosQuant[[col_name]])) {
dadosQuali[[col_name]] <- as.factor(transform_to_categories(dadosQuant[[col_name]]))
dadosQuant[[col_name]] <- NULL
cat(sprintf("Transformed column '%s' into categories\n", col_name))
}
}
}## Transformed column 'x1' into categories
## Transformed column 'x3' into categories
## Transformed column 'x4' into categories
## Transformed column 'x6' into categories
## Transformed column 'x7' into categories
## Transformed column 'x8' into categories
## Transformed column 'x9' into categories
## Transformed column 'x10' into categories
## Transformed column 'x11' into categories
## Transformed column 'x12' into categories
## Transformed column 'x15' into categories
## Transformed column 'x16' into categories
## Transformed column 'x17' into categories
## Transformed column 'x19' into categories
## Transformed column 'x23' into categories
## Transformed column 'x24' into categories
## Transformed column 'x25' into categories
## Transformed column 'x26' into categories
## Transformed column 'x29' into categories
## Transformed column 'x30' into categories
## Transformed column 'x31' into categories
## Transformed column 'x32' into categories
## Transformed column 'x33' into categories
## Transformed column 'x35' into categories
## Transformed column 'x36' into categories
## Transformed column 'x37' into categories
## Transformed column 'x38' into categories
## Transformed column 'x39' into categories
## Transformed column 'x40' into categories
## Transformed column 'x41' into categories
## Transformed column 'x42' into categories
## Transformed column 'x43' into categories
## Transformed column 'x44' into categories
## Transformed column 'x46' into categories
## Transformed column 'x47' into categories
## Transformed column 'x48' into categories
## Transformed column 'x49' into categories
## Transformed column 'x51' into categories
## Transformed column 'x52' into categories
## Transformed column 'x54' into categories
## Transformed column 'x55' into categories
## Transformed column 'x57' into categories
## Transformed column 'x58' into categories
## Transformed column 'x60' into categories
## Transformed column 'x61' into categories
## Transformed column 'x63' into categories
## Transformed column 'x64' into categories
## Transformed column 'x65' into categories
## Transformed column 'x66' into categories
## Transformed column 'x68' into categories
## Transformed column 'x69' into categories
## Transformed column 'x70' into categories
## Transformed column 'x71' into categories
## Transformed column 'x73' into categories
## Transformed column 'x76' into categories
## Transformed column 'x77' into categories
## Transformed column 'x79' into categories
## Transformed column 'x80' into categories
## Transformed column 'x81' into categories
## Transformed column 'x84' into categories
## Transformed column 'x85' into categories
## Transformed column 'x86' into categories
## Transformed column 'x87' into categories
## Transformed column 'x88' into categories
## Transformed column 'x89' into categories
## Transformed column 'x93' into categories
## Transformed column 'x95' into categories
## Transformed column 'x96' into categories
## Transformed column 'x97' into categories
## Transformed column 'x98' into categories
## Transformed column 'x99' into categories
## Transformed column 'x102' into categories
## Transformed column 'x103' into categories
## Transformed column 'x104' into categories
## Transformed column 'x106' into categoriesNormalizando os dados quantitativos que não apresentaram outliers para o treinamento do modelo
# Normalização para o intervalo [0, 1]
df_norm <- dadosQuant %>%
# select(-target) %>%
mutate(across(everything(), ~(. - min(.)) / (max(.) - min(.))))Análise de correlacao de Pearson para variaveis quantitativas que não possuem outlier
# selecionar somente as variaveis quantitativas
df_corr <- cbind(df_norm,target)
correlacao <- cor(df_corr)
correlacao## x13 x14 x18 x20 x21
## x13 1.00000000000 -0.00598272551 -0.0037602424 -0.0022639848 -0.004596051
## x14 -0.00598272551 1.00000000000 -0.0042285731 -0.0029249558 0.002036772
## x18 -0.00376024238 -0.00422857312 1.0000000000 -0.0054865605 -0.001034281
## x20 -0.00226398483 -0.00292495581 -0.0054865605 1.0000000000 0.001606259
## x21 -0.00459605084 0.00203677191 -0.0010342814 0.0016062593 1.000000000
## x22 -0.00008053166 0.00016023451 -0.0118438760 -0.0047334351 0.014536422
## x34 -0.00953778523 0.00534132459 0.0073717893 -0.0009417172 -0.002492874
## x45 -0.00903454197 0.00746630224 -0.0002073913 0.0065096791 0.006165096
## x50 -0.00788729475 -0.00260211289 0.0016405970 0.0077699132 -0.009060700
## x56 0.00590460432 -0.00340278568 0.0088211426 0.0041904956 -0.001386876
## x72 0.00169984059 0.00800765914 0.0056380057 -0.0146491428 -0.003797914
## x74 -0.00520809340 -0.00007245535 -0.0099645502 0.0070827686 0.015737275
## x75 -0.00432361410 -0.00464059215 0.0104857950 0.1152482919 -0.012584604
## x82 -0.01631469054 0.00573777528 0.0018167358 -0.0014314216 0.008069647
## x83 -0.00165416904 -0.00993980638 0.0041580712 0.0024250334 -0.007503694
## x90 -0.00853386638 -0.00187285765 0.0015919383 0.0072413220 -0.009166028
## x92 -0.00025690679 -0.00008627035 -0.0117490951 -0.0048173844 0.014755992
## x94 -0.00258902431 -0.00343299960 -0.0031578495 0.0031112847 -0.004372723
## x101 -0.00226838870 -0.00291378800 -0.0054679966 0.9999987980 0.001626191
## x105 -0.00228853719 -0.00291321011 0.9800415672 -0.0055062632 0.001122327
## target -0.06715429390 0.00790445806 0.1452504090 -0.2158846790 -0.012575161
## x22 x34 x45 x50 x56
## x13 -0.00008053166 -0.0095377852 -0.0090345420 -0.0078872947 0.00590460432
## x14 0.00016023451 0.0053413246 0.0074663022 -0.0026021129 -0.00340278568
## x18 -0.01184387598 0.0073717893 -0.0002073913 0.0016405970 0.00882114261
## x20 -0.00473343511 -0.0009417172 0.0065096791 0.0077699132 0.00419049558
## x21 0.01453642176 -0.0024928735 0.0061650959 -0.0090607002 -0.00138687647
## x22 1.00000000000 -0.0094208876 0.0041934812 -0.0063576533 -0.00302503110
## x34 -0.00942088765 1.0000000000 -0.0048237239 0.0025220260 0.00447409226
## x45 0.00419348118 -0.0048237239 1.0000000000 -0.0048712593 0.00262203861
## x50 -0.00635765329 0.0025220260 -0.0048712593 1.0000000000 0.00047677425
## x56 -0.00302503110 0.0044740923 0.0026220386 0.0004767743 1.00000000000
## x72 -0.00095757771 -0.0010341108 -0.0029852720 0.0006367332 -0.00001298569
## x74 0.00022795502 0.0030486205 0.0159292408 -0.0027103459 0.00795898854
## x75 0.00597101367 -0.0106605471 0.0016876846 -0.0036602641 0.00399255164
## x82 -0.00879022669 0.0010324911 -0.0016566013 -0.0017651893 0.00140213836
## x83 0.00686237553 0.0051527378 -0.0025616123 0.0047557437 0.00477399282
## x90 -0.00642709697 0.0025243147 -0.0053147533 0.9985249883 0.00068894189
## x92 0.99963861574 -0.0096493777 0.0042182701 -0.0064517063 -0.00310447615
## x94 -0.00334997976 -0.0062194707 0.0006898639 -0.0090652502 -0.00478078074
## x101 -0.00473764814 -0.0009344124 0.0065085650 0.0077687677 0.00422788260
## x105 -0.01078186241 0.0089623676 0.0009217907 0.0002719618 0.00969426392
## target 0.01167759203 0.0148289084 -0.1346590433 -0.0873657660 0.03729793409
## x72 x74 x75 x82 x83
## x13 0.00169984059 -0.00520809340 -0.004323614 -0.016314691 -0.0016541690
## x14 0.00800765914 -0.00007245535 -0.004640592 0.005737775 -0.0099398064
## x18 0.00563800567 -0.00996455018 0.010485795 0.001816736 0.0041580712
## x20 -0.01464914276 0.00708276858 0.115248292 -0.001431422 0.0024250334
## x21 -0.00379791352 0.01573727519 -0.012584604 0.008069647 -0.0075036943
## x22 -0.00095757771 0.00022795502 0.005971014 -0.008790227 0.0068623755
## x34 -0.00103411083 0.00304862049 -0.010660547 0.001032491 0.0051527378
## x45 -0.00298527195 0.01592924081 0.001687685 -0.001656601 -0.0025616123
## x50 0.00063673321 -0.00271034590 -0.003660264 -0.001765189 0.0047557437
## x56 -0.00001298569 0.00795898854 0.003992552 0.001402138 0.0047739928
## x72 1.00000000000 -0.00116963418 0.003685356 -0.003697962 0.0030294716
## x74 -0.00116963418 1.00000000000 -0.001823967 0.004718025 0.0002341786
## x75 0.00368535632 -0.00182396747 1.000000000 -0.008772800 0.0067373176
## x82 -0.00369796175 0.00471802487 -0.008772800 1.000000000 0.0114305186
## x83 0.00302947159 0.00023417864 0.006737318 0.011430519 1.0000000000
## x90 0.00128709978 -0.00211409964 -0.003428911 -0.001822815 0.0045040888
## x92 -0.00118396614 0.00003180002 0.006065699 -0.008998138 0.0066496635
## x94 0.00313814445 -0.00863650824 0.004916130 0.004127002 -0.0065767353
## x101 -0.01466961350 0.00708863885 0.115240394 -0.001429513 0.0024346589
## x105 0.00580264588 -0.00927725635 0.009450146 -0.001656447 0.0071582652
## target 0.01188435440 -0.01720474421 -0.155972836 -0.105159738 0.0304525124
## x90 x92 x94 x101 x105
## x13 -0.0085338664 -0.00025690679 -0.0025890243 -0.0022683887 -0.0022885372
## x14 -0.0018728576 -0.00008627035 -0.0034329996 -0.0029137880 -0.0029132101
## x18 0.0015919383 -0.01174909514 -0.0031578495 -0.0054679966 0.9800415672
## x20 0.0072413220 -0.00481738438 0.0031112847 0.9999987980 -0.0055062632
## x21 -0.0091660280 0.01475599194 -0.0043727232 0.0016261905 0.0011223270
## x22 -0.0064270970 0.99963861574 -0.0033499798 -0.0047376481 -0.0107818624
## x34 0.0025243147 -0.00964937767 -0.0062194707 -0.0009344124 0.0089623676
## x45 -0.0053147533 0.00421827011 0.0006898639 0.0065085650 0.0009217907
## x50 0.9985249883 -0.00645170628 -0.0090652502 0.0077687677 0.0002719618
## x56 0.0006889419 -0.00310447615 -0.0047807807 0.0042278826 0.0096942639
## x72 0.0012870998 -0.00118396614 0.0031381445 -0.0146696135 0.0058026459
## x74 -0.0021140996 0.00003180002 -0.0086365082 0.0070886388 -0.0092772564
## x75 -0.0034289114 0.00606569944 0.0049161305 0.1152403936 0.0094501465
## x82 -0.0018228145 -0.00899813781 0.0041270022 -0.0014295125 -0.0016564474
## x83 0.0045040888 0.00664966354 -0.0065767353 0.0024346589 0.0071582652
## x90 1.0000000000 -0.00653577516 -0.0092887035 0.0072404216 0.0001420905
## x92 -0.0065357752 1.00000000000 -0.0034806790 -0.0048211111 -0.0107083671
## x94 -0.0092887035 -0.00348067902 1.0000000000 0.0031129304 -0.0061978896
## x101 0.0072404216 -0.00482111111 0.0031129304 1.0000000000 -0.0054868242
## x105 0.0001420905 -0.01070836711 -0.0061978896 -0.0054868242 1.0000000000
## target -0.0875410773 0.01156129594 0.1496535008 -0.2158469989 0.1437556049
## target
## x13 -0.067154294
## x14 0.007904458
## x18 0.145250409
## x20 -0.215884679
## x21 -0.012575161
## x22 0.011677592
## x34 0.014828908
## x45 -0.134659043
## x50 -0.087365766
## x56 0.037297934
## x72 0.011884354
## x74 -0.017204744
## x75 -0.155972836
## x82 -0.105159738
## x83 0.030452512
## x90 -0.087541077
## x92 0.011561296
## x94 0.149653501
## x101 -0.215846999
## x105 0.143755605
## target 1.000000000mc <- correlacaoMatriz de correlação das variaveis quantitativas com a target
library(corrplot)## Warning: package 'corrplot' was built under R version 4.3.1## corrplot 0.92 loaded#corrplot(mc)
corrplot(mc, type="full", method="number")
Variaveis qualitativas
Criando as variaveis dummy
# Criar uma lista de todas as colunas categóricas, exceto 'x5'
# columns_to_dummy <- setdiff(names(dadosQuali), c("x5", "x28", "x67"))
# criar variaveis dummies das variaveis preditoras qualitativas
var_dummies <- dummy_cols(dadosQuali, select_columns = names(dadosQuali),
remove_first_dummy = TRUE,
remove_selected_columns = TRUE)df_modelo <- cbind(df_norm,var_dummies,target)g) Selecionar as variáveis preditoras.
Apos o tratamento dos dados temos um dataframe com 4261 variaveis preditoras.
paste("Preditoras:",length(names(df_modelo))-1)## [1] "Preditoras: 4261"h) Definir a variável resposta.
Apos o tratamento dos dados temos um dataframe com 1 coluna target.
paste("Target",length(names(df_modelo))-4261)## [1] "Target 1"i) Rodar o modelo de Regressão Linear Múltipla.
Dividir a amostra em treino e validação (70/30 %)
#Dividir em duas amostras
set.seed(1010)
train <- sample(nrow(df_modelo), 0.7*nrow(df_modelo), replace = FALSE)
TrainSet <- df_modelo[train,]
ValidSet <- df_modelo[-train,]Comparar a variável resposta nas duas amostras
summary(TrainSet$target)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.2398 0.5005 0.9821 1.6508 1.9589 48.5965summary(ValidSet$target)## Min. 1st Qu. Median Mean 3rd Qu. Max.
## -0.1290 0.5129 0.9862 1.6842 1.9905 61.3261Rodar o modelo inicial
modelo_inicial <- lm(target ~ ., data = TrainSet)
summary(modelo_inicial)##
## Call:
## lm(formula = target ~ ., data = TrainSet)
##
## Residuals:
## Min 1Q Median 3Q Max
## -6.263 -0.732 -0.087 0.568 32.877
##
## Coefficients: (89 not defined because of singularities)
## Estimate Std. Error t value
## (Intercept) 0.5270584 7.7290136 0.068
## x13 -0.4510313 0.0479707 -9.402
## x14 0.1976822 0.1157190 1.708
## x18 0.6147126 0.2296959 2.676
## x20 -23.6290012 37.2948012 -0.634
## x21 -0.0703798 0.0603986 -1.165
## x22 1.9141182 1.8482064 1.036
## x34 0.1491648 0.0579955 2.572
## x45 -1.0556747 0.0480701 -21.961
## x50 0.5655866 0.8765531 0.645
## x56 0.2482660 0.0427724 5.804
## x72 0.0693856 0.0484568 1.432
## x74 -0.0602486 0.0479731 -1.256
## x75 -0.8248548 0.0396663 -20.795
## x82 -0.8042306 0.0481439 -16.705
## x83 0.2665450 0.0484873 5.497
## x90 -1.0917525 0.8119578 -1.345
## x92 -1.9303453 1.9642209 -0.983
## x94 1.1582002 0.0483253 23.967
## x101 22.3329211 37.1610579 0.601
## x105 0.6025539 0.3115962 1.934
## x2_009fdc2d37ffaba8e9854e5bf91e8193 1.3862385 0.4517400 3.069
## x2_0104f035fa3fd6867f97188b1f126c91 0.9529533 0.4567179 2.087
## x2_014498d37e0e50ffbd27edb7b87a02ce 1.2934600 0.4476324 2.890
## x2_01b5b97a96c69e9ee73b325b21a1093e 1.4694070 0.4542477 3.235
## x2_02949cb2e4502b1c382f48731eaa5d7d 1.8803891 0.4773993 3.939
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.9604041 0.4520202 2.125
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 -0.0374329 0.4714890 -0.079
## x2_03af349e980524ba204e4fdd09583887 -0.4059218 0.4828075 -0.841
## x2_03b7592ee764f088fa73a5964181d3eb 0.6431600 0.4969407 1.294
## x2_03be585b1ec66610133d1e369ea0bae0 0.3202526 0.4363937 0.734
## x2_044c0dccd777a21ad32dfa271b25b05d -0.7942277 0.4600567 -1.726
## x2_04b5a9fbcede6d8da2c9443a74659508 0.0489621 0.4988109 0.098
## x2_050e1afffbd1d7a2ae2d692e664e8cc6 -0.1770219 0.4285971 -0.413
## x2_051d67c71a408ff3d1c5ef12bd4c4beb -0.2530474 0.4595564 -0.551
## x2_0527609acb9d3bb9f16229e4ea213155 0.6698597 0.4661613 1.437
## x2_053921d1e61fda98664a7cbc984b73bc 0.9549783 0.4475607 2.134
## x2_055310e43ac25f3e7ce8d0197c029b05 0.8873427 0.5255476 1.688
## x2_05d62a51dc2cdb45015ac40846de7d2f -0.2763893 0.4360758 -0.634
## x2_063949e8aa1746c2f2072e3c3dfdf072 1.5247399 0.4926631 3.095
## x2_06970c71617ff7923b250ac7ca9487a4 0.9370542 0.4284380 2.187
## x2_06fee204db920d6132334a5c3022b7f1 0.0688002 0.4511373 0.153
## x2_087911c45b61db3e68a882004e37718c 1.3140514 0.4751331 2.766
## x2_08858f31ce8691322fa038d8660cf83e -0.0810008 0.4577802 -0.177
## x2_08e6c24b07efe1adef6bb2e463299f2d 2.4678600 0.5201984 4.744
## x2_0a28dc4bccab65e38f0c53ba789c83ed -0.2849444 0.4412583 -0.646
## x2_0a69cf48a1af11b4d7a7ef215ffe8622 0.1499638 0.4570655 0.328
## x2_0a72af1fa112ba359d30fee41d5f93fb -0.7159582 0.4375072 -1.636
## x2_0bc010c231ab369fff9c24dcb493a691 -0.5311733 0.5576686 -0.952
## x2_0bda5d7eb1821a2ee9ad763276d4506e -0.2788505 0.4551910 -0.613
## x2_0c9e2bc33a3f374bb3640162acb5d17f -0.7765166 0.4716393 -1.646
## x2_0d07f17e244a25eb185c35a74c8933fd -0.6227693 0.5067973 -1.229
## x2_0dc4cab512b3206e5e1bc6cb09979f45 -0.0119597 0.4335514 -0.028
## x2_0f485cf337eda5dd5944bec5a0b06ddf 1.3171519 0.4390734 3.000
## x2_0f7c19f51275e21407c8ce1288245eb2 0.0749997 0.4687448 0.160
## x2_0feb9fe6a7fb9cdb87eb1d9fee3551aa -0.2741041 0.4675888 -0.586
## x2_104bee6dd94618d74bb624495714051f 0.4099003 0.4581723 0.895
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## x8_16 NA NA NA
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## x10_3 -0.1284710 0.1585030 -0.811
## x10_4 -0.1822197 0.1571327 -1.160
## x10_5 -0.1901871 0.1573291 -1.209
## x10_6 -0.1753275 0.1577222 -1.112
## x10_7 -0.2085924 0.1602399 -1.302
## x10_8 -0.1763914 0.1638569 -1.076
## x10_9 0.0662221 0.1706325 0.388
## x10_10 -0.0061195 0.1919033 -0.032
## x10_11 -0.0256909 0.2303113 -0.112
## x10_12 0.1222059 0.2933300 0.417
## x10_13 0.1494494 0.4111260 0.364
## x10_14 0.1510481 0.6422589 0.235
## x10_15 -0.1275040 0.7631324 -0.167
## x10_16 1.3802033 0.9434966 1.463
## x11_2 -0.0078017 0.0318517 -0.245
## x11_3 0.0481902 0.0423699 1.137
## x11_4 0.1729340 0.0674768 2.563
## x11_5 0.1449752 0.1047864 1.384
## x11_6 0.4203679 0.1712695 2.454
## x11_7 0.2458007 0.2555660 0.962
## x11_8 0.3323916 0.4320492 0.769
## x11_9 0.1207371 0.4986582 0.242
## x11_10 0.6449745 1.3095770 0.493
## x11_11 0.4392306 1.1206162 0.392
## x11_12 2.4450728 1.7927174 1.364
## x11_15 -0.1081657 1.2798413 -0.085
## x11_16 1.8244465 1.2852010 1.420
## x12_2 0.0483797 0.8195143 0.059
## x12_3 -0.3369453 0.7219056 -0.467
## x12_4 -0.2862588 0.6656731 -0.430
## x12_5 0.2424714 0.6533813 0.371
## x12_6 0.1648363 0.6476025 0.255
## x12_7 -0.0362472 0.6449604 -0.056
## x12_8 0.1555802 0.6436632 0.242
## x12_9 0.0129800 0.6432299 0.020
## x12_10 0.0385732 0.6430051 0.060
## x12_11 0.1016027 0.6429333 0.158
## x12_12 0.0866034 0.6432241 0.135
## x12_13 0.1089544 0.6435857 0.169
## x12_14 0.0778760 0.6463736 0.120
## x12_15 -0.1385683 0.6624603 -0.209
## x12_16 -0.3269406 0.7737244 -0.423
## x15_2 -1.8925740 1.5226516 -1.243
## x15_3 -1.5715154 1.3231925 -1.188
## x15_4 -1.2467493 1.2952411 -0.963
## x15_5 -1.2762184 1.2906674 -0.989
## x15_6 -1.2898637 1.2891616 -1.001
## x15_7 -1.2644805 1.2888200 -0.981
## x15_8 -1.3181639 1.2885131 -1.023
## x15_9 -1.3642314 1.2885774 -1.059
## x15_10 -1.3836767 1.2886755 -1.074
## x15_11 -1.4954131 1.2889584 -1.160
## x15_12 -1.2674947 1.2904434 -0.982
## x15_13 -1.4729516 1.2935046 -1.139
## x15_14 -1.3872363 1.3145625 -1.055
## x15_15 -1.4000039 1.5219588 -0.920
## x15_16 -2.5999265 1.8215947 -1.427
## x16_2 -1.3140901 0.6947196 -1.892
## x16_3 -1.8692166 0.6389342 -2.926
## x16_4 -2.0647307 0.6175533 -3.343
## x16_5 -2.0657659 0.6161509 -3.353
## x16_6 -2.0033696 0.6162846 -3.251
## x16_7 -2.0865161 0.6176736 -3.378
## x16_8 -2.0061288 0.6172277 -3.250
## x16_9 -2.0319808 0.6175099 -3.291
## x16_10 -1.9760733 0.6184115 -3.195
## x16_11 -1.8409505 0.6198559 -2.970
## x16_12 -1.8501900 0.6245933 -2.962
## x16_13 -1.9908437 0.6398943 -3.111
## x16_14 -1.9419556 0.6846877 -2.836
## x16_15 -1.7291209 0.8453539 -2.045
## x16_16 -1.8673388 1.2770743 -1.462
## x17_2 -0.0291695 0.0345810 -0.844
## x17_3 -0.0232295 0.0429551 -0.541
## x17_4 -0.0750511 0.0568159 -1.321
## x17_5 -0.1150212 0.0741502 -1.551
## x17_6 0.0583380 0.1096857 0.532
## x17_7 -0.0798409 0.1410477 -0.566
## x17_8 -0.2099040 0.1840274 -1.141
## x17_9 -0.2234283 0.2593234 -0.862
## x17_10 0.2820183 0.3353797 0.841
## x17_11 0.4028570 0.4003543 1.006
## x17_12 0.7063349 0.7417815 0.952
## x17_13 -0.2932435 1.0621260 -0.276
## x17_14 -1.2747432 1.8267361 -0.698
## x17_15 0.8990244 1.0525818 0.854
## x17_16 -1.2904872 1.8915674 -0.682
## x19_2 0.8826518 1.0341763 0.853
## x19_3 0.2782539 0.9493012 0.293
## x19_4 0.6365285 0.9307123 0.684
## x19_5 0.4284713 0.9256609 0.463
## x19_6 0.4366172 0.9224761 0.473
## x19_7 0.4861985 0.9232484 0.527
## x19_8 0.4862265 0.9233640 0.527
## x19_9 0.4665480 0.9236542 0.505
## x19_10 0.4450490 0.9238193 0.482
## x19_11 0.3545855 0.9246763 0.383
## x19_12 0.3978909 0.9264354 0.429
## x19_13 0.6472185 0.9313039 0.695
## x19_14 0.9476581 0.9521711 0.995
## x19_15 0.6148472 1.0159170 0.605
## x19_16 -2.9245371 2.0306216 -1.440
## x23_2 0.0620611 2.0908332 0.030
## x23_3 0.6186189 1.8703936 0.331
## x23_4 0.7217016 1.8117231 0.398
## x23_5 0.2993583 1.8016125 0.166
## x23_6 0.4394391 1.7997364 0.244
## x23_7 0.5034331 1.7984103 0.280
## x23_8 0.4944115 1.7989228 0.275
## x23_9 0.3778309 1.7989080 0.210
## x23_10 0.3745389 1.7991594 0.208
## x23_11 0.4646706 1.7994273 0.258
## x23_12 0.4487035 1.8000724 0.249
## x23_13 0.5157313 1.8057287 0.286
## x23_14 0.7725842 1.8245067 0.423
## x23_15 2.0029900 1.8834194 1.063
## x23_16 0.2113433 2.3017942 0.092
## x24_2 -0.3290331 0.0769233 -4.277
## x24_3 -0.4781347 0.2114187 -2.262
## x24_4 -0.4160804 0.4055061 -1.026
## x24_5 -0.5117429 1.1503960 -0.445
## x24_6 -1.3422321 1.4009246 -0.958
## x24_7 -1.0775426 2.3214102 -0.464
## x24_8 -1.8170395 2.6204622 -0.693
## x24_9 -3.0989924 3.3409177 -0.928
## x24_10 1.1671739 1.9114848 0.611
## x24_11 0.2430070 1.2788365 0.190
## x24_12 -0.3373500 1.8121871 -0.186
## x24_14 1.4643552 1.8000303 0.814
## x24_16 6.5298270 1.8191624 3.589
## x25_2 -0.2326490 0.0487029 -4.777
## x25_3 -0.7031944 0.0497751 -14.127
## x25_4 -0.7508581 0.0524334 -14.320
## x25_5 -0.7932769 0.0586547 -13.525
## x25_6 -0.7063273 0.0678998 -10.402
## x25_7 -0.6419018 0.0823359 -7.796
## x25_8 -0.5733258 0.1004876 -5.705
## x25_9 -0.3179069 0.1278218 -2.487
## x25_10 -0.1482969 0.1870101 -0.793
## x25_11 -0.5843669 0.2190939 -2.667
## x25_12 -0.1205023 0.2927979 -0.412
## x25_13 -0.9638275 0.3619897 -2.663
## x25_14 -1.0908379 0.6483364 -1.683
## x25_15 -1.3955336 0.8195335 -1.703
## x25_16 -0.4964565 1.2906866 -0.385
## x26_2 -0.3584676 0.2398434 -1.495
## x26_3 -0.4250592 0.2276714 -1.867
## x26_4 -0.3902647 0.2227405 -1.752
## x26_5 -0.3835613 0.2215279 -1.731
## x26_6 -0.3401890 0.2203511 -1.544
## x26_7 -0.4307446 0.2200579 -1.957
## x26_8 -0.3231812 0.2203517 -1.467
## x26_9 -0.4016377 0.2208426 -1.819
## x26_10 -0.3418099 0.2222557 -1.538
## x26_11 -0.3015376 0.2256420 -1.336
## x26_12 -0.3355008 0.2334325 -1.437
## x26_13 -0.3289616 0.2584619 -1.273
## x26_14 -0.4373377 0.3347760 -1.306
## x26_15 -0.2787736 0.4280793 -0.651
## x26_16 -1.9044510 1.8410823 -1.034
## x29_2 0.1315918 0.1501471 0.876
## x29_3 -0.1155654 0.4128424 -0.280
## x29_4 -0.1355203 0.9249566 -0.147
## x29_5 0.7975031 1.7586298 0.453
## x29_6 1.5457633 2.0880379 0.740
## x29_7 1.0369590 2.3955564 0.433
## x29_8 2.4629951 2.7756248 0.887
## x29_9 7.9796860 3.4211862 2.332
## x29_10 NA NA NA
## x29_11 NA NA NA
## x29_12 NA NA NA
## x29_14 NA NA NA
## x29_16 NA NA NA
## x30_2 0.5403619 0.9739538 0.555
## x30_3 0.8008036 0.9251993 0.866
## x30_4 0.5259928 0.9182418 0.573
## x30_5 0.6526638 0.9160928 0.712
## x30_6 0.6034302 0.9152056 0.659
## x30_7 0.5143265 0.9145304 0.562
## x30_8 0.5446879 0.9146546 0.596
## x30_9 0.5602467 0.9147388 0.612
## x30_10 0.5142732 0.9146157 0.562
## x30_11 0.5894734 0.9159684 0.644
## x30_12 0.6433834 0.9184853 0.700
## x30_13 0.3457040 0.9249956 0.374
## x30_14 0.6461113 0.9507226 0.680
## x30_15 0.3262282 1.0292643 0.317
## x30_16 NA NA NA
## x31_2 -0.8024134 0.4817034 -1.666
## x31_3 -0.5692416 0.4636922 -1.228
## x31_4 -0.5943687 0.4610664 -1.289
## x31_5 -0.5844800 0.4614759 -1.267
## x31_6 -0.6114718 0.4620144 -1.323
## x31_7 -0.5511905 0.4634610 -1.189
## x31_8 -0.6175105 0.4648148 -1.329
## x31_9 -0.6768383 0.4677962 -1.447
## x31_10 -0.6925294 0.4717024 -1.468
## x31_11 -0.7556932 0.4836165 -1.563
## x31_12 -0.7481246 0.5085812 -1.471
## x31_13 -0.7361088 0.5633710 -1.307
## x31_14 -0.5549647 0.7093413 -0.782
## x31_15 -0.4527408 1.0414638 -0.435
## x31_16 -0.0620638 1.4148462 -0.044
## x32_2 0.0952032 0.4336596 0.220
## x32_3 0.2994185 0.8686467 0.345
## x32_4 0.0331792 0.0601531 0.552
## x32_5 -2.8613226 1.8256727 -1.567
## x32_6 -0.0434383 0.1106675 -0.393
## x32_7 0.6706734 1.8211979 0.368
## x32_8 0.2499334 0.2350762 1.063
## x32_9 -0.3631177 0.2851392 -1.273
## x32_10 0.1400342 0.4702905 0.298
## x32_11 0.2134789 0.5077939 0.420
## x32_12 0.4101518 1.1545783 0.355
## x32_13 0.2097621 1.0482188 0.200
## x32_14 2.5022792 1.8451397 1.356
## x32_16 -0.5401913 1.8012683 -0.300
## x33_2 0.2086375 0.2064606 1.011
## x33_3 0.1817258 0.1992531 0.912
## x33_4 0.1766972 0.1974843 0.895
## x33_5 0.1705675 0.1972615 0.865
## x33_6 0.1653341 0.1978387 0.836
## x33_7 0.1292514 0.1990518 0.649
## x33_8 0.1051841 0.2015307 0.522
## x33_9 0.3412931 0.2067559 1.651
## x33_10 0.1875389 0.2171339 0.864
## x33_11 0.2986178 0.2490738 1.199
## x33_12 0.2762241 0.3044896 0.907
## x33_13 0.2888706 0.4213497 0.686
## x33_14 1.0412001 0.5770398 1.804
## x33_15 0.5815323 0.8450991 0.688
## x33_16 1.7761716 1.3343468 1.331
## x35_7 -0.9557111 2.6414743 -0.362
## x35_8 1.1899311 1.9072092 0.624
## x35_9 1.2506664 2.6472262 0.472
## x35_16 NA NA NA
## x36_2 -0.0318986 0.0357376 -0.893
## x36_3 0.0060299 0.0430249 0.140
## x36_4 0.0347969 0.0539172 0.645
## x36_5 0.1159117 0.0665140 1.743
## x36_6 -0.0504037 0.0831181 -0.606
## x36_7 0.1321958 0.1054527 1.254
## x36_8 0.0703941 0.1444904 0.487
## x36_9 0.1250081 0.1818477 0.687
## x36_10 0.0369057 0.2138704 0.173
## x36_11 -0.3192760 0.2978981 -1.072
## x36_12 -0.2161104 0.3814762 -0.567
## x36_13 -0.5246868 0.4886383 -1.074
## x36_14 0.3357944 0.6125503 0.548
## x36_15 0.2762529 0.8123073 0.340
## x36_16 -0.0341128 1.0517755 -0.032
## x37_2 -0.0388377 1.3663039 -0.028
## x37_15 -0.0417013 0.0524485 -0.795
## x37_16 -0.2447866 0.2387128 -1.025
## x38_2 0.1255974 0.5533016 0.227
## x38_3 0.2447652 0.5218687 0.469
## x38_4 -0.0267662 0.5072968 -0.053
## x38_5 0.1431804 0.5043320 0.284
## x38_6 -0.0990081 0.5032730 -0.197
## x38_7 -0.0859988 0.5026731 -0.171
## x38_8 -0.1612598 0.5024247 -0.321
## x38_9 -0.0807958 0.5025801 -0.161
## x38_10 -0.1311613 0.5025024 -0.261
## x38_11 -0.0999193 0.5044442 -0.198
## x38_12 -0.1687808 0.5082580 -0.332
## x38_13 -0.3409374 0.5200965 -0.656
## x38_14 0.0297362 0.5623275 0.053
## x38_15 -0.5929026 0.7142327 -0.830
## x38_16 0.2920469 1.1771656 0.248
## x39_2 -0.8821718 1.4349864 -0.615
## x39_3 -0.4960360 1.3427024 -0.369
## x39_4 -0.3227906 1.3170572 -0.245
## x39_5 -0.3504643 1.3133471 -0.267
## x39_6 -0.3828567 1.3118856 -0.292
## x39_7 -0.3038546 1.3112918 -0.232
## x39_8 -0.2509421 1.3112669 -0.191
## x39_9 0.0383275 1.3113579 0.029
## x39_10 0.2662031 1.3113036 0.203
## x39_11 0.3811988 1.3114131 0.291
## x39_12 0.3235942 1.3123237 0.247
## x39_13 0.4269417 1.3146499 0.325
## x39_14 0.5869671 1.3251864 0.443
## x39_15 2.8420934 1.3928354 2.041
## x39_16 -1.6180623 2.2409738 -0.722
## x40_2 0.9674186 1.8960144 0.510
## x40_3 1.3504044 1.8273252 0.739
## x40_4 0.8061084 1.8157912 0.444
## x40_5 0.9721533 1.8130205 0.536
## x40_6 1.0346492 1.8121851 0.571
## x40_7 0.9667437 1.8119378 0.534
## x40_8 1.1311991 1.8118027 0.624
## x40_9 1.1610359 1.8118728 0.641
## x40_10 1.1642464 1.8120997 0.642
## x40_11 1.2616736 1.8127716 0.696
## x40_12 1.7112223 1.8139264 0.943
## x40_13 1.4533155 1.8177681 0.800
## x40_14 1.6859322 1.8407725 0.916
## x40_15 0.8511816 1.8934598 0.450
## x40_16 0.8518565 2.5875110 0.329
## x41_2 -0.1710599 0.2404818 -0.711
## x41_3 -0.0979650 0.2311413 -0.424
## x41_4 -0.1983267 0.2278143 -0.871
## x41_5 -0.1641807 0.2270321 -0.723
## x41_6 -0.1443158 0.2265841 -0.637
## x41_7 -0.2332879 0.2264349 -1.030
## x41_8 -0.1035346 0.2268780 -0.456
## x41_9 -0.1913030 0.2279244 -0.839
## x41_10 -0.0938958 0.2304736 -0.407
## x41_11 0.0745909 0.2359952 0.316
## x41_12 0.1510480 0.2470747 0.611
## x41_13 0.1188929 0.2816170 0.422
## x41_14 0.3105549 0.3860510 0.804
## x41_15 0.6368361 0.7773837 0.819
## x41_16 0.1026935 0.9360252 0.110
## x42_2 -0.0072373 0.0344495 -0.210
## x42_3 0.0434408 0.0434130 1.001
## x42_4 0.0173646 0.0566418 0.307
## x42_5 -0.1660563 0.0754985 -2.199
## x42_6 -0.0336242 0.0988802 -0.340
## x42_7 0.0314429 0.2506743 0.125
## x42_8 0.0384659 0.2830610 0.136
## x42_9 0.2207477 0.3130869 0.705
## x42_10 0.2453837 0.3724709 0.659
## x42_11 -0.0685077 0.4661374 -0.147
## x42_12 0.2530991 0.6255611 0.405
## x42_13 0.8519478 0.7331175 1.162
## x42_14 0.8288922 1.0827835 0.766
## x42_15 -0.6614215 1.8673853 -0.354
## x42_16 -1.0211366 1.8289671 -0.558
## x43_2 0.6012595 1.0813076 0.556
## x43_3 0.5302979 0.9860871 0.538
## x43_4 0.5427626 0.9482023 0.572
## x43_5 0.4923580 0.9474420 0.520
## x43_6 0.4819181 0.9476979 0.509
## x43_7 0.5066259 0.9479001 0.534
## x43_8 0.5879991 0.9480044 0.620
## x43_9 0.5181934 0.9480734 0.547
## x43_10 0.5153078 0.9489207 0.543
## x43_11 0.4418043 0.9505625 0.465
## x43_12 0.6621540 0.9551297 0.693
## x43_13 0.3503656 0.9659131 0.363
## x43_14 0.4391896 1.0181454 0.431
## x43_15 1.1368160 1.4107841 0.806
## x43_16 NA NA NA
## x44_2 0.1380547 1.1634167 0.119
## x44_3 0.4469270 1.0861879 0.411
## x44_4 0.4036045 1.0610593 0.380
## x44_5 0.3849914 1.0525185 0.366
## x44_6 0.3691291 1.0496591 0.352
## x44_7 0.4409890 1.0503265 0.420
## x44_8 0.3437093 1.0507106 0.327
## x44_9 0.5007683 1.0504917 0.477
## x44_10 0.5617910 1.0509703 0.535
## x44_11 0.5545139 1.0514203 0.527
## x44_12 0.4715329 1.0537748 0.447
## x44_13 0.6399077 1.0617487 0.603
## x44_14 0.7464669 1.0919774 0.684
## x44_15 0.0982208 1.1843636 0.083
## x44_16 -2.6226003 2.1277107 -1.233
## x46_2 -0.0622182 0.2943767 -0.211
## x46_3 -0.0684840 0.2943293 -0.233
## x46_4 -0.0764309 0.2948082 -0.259
## x46_5 -0.0151179 0.2949072 -0.051
## x46_6 0.0284750 0.2963951 0.096
## x46_7 -0.0296903 0.2993411 -0.099
## x46_8 -0.1789047 0.3074845 -0.582
## x46_9 -0.1499966 0.3248253 -0.462
## x46_10 -0.3422632 0.3594649 -0.952
## x46_11 0.3515150 0.4628310 0.759
## x46_12 -0.4896635 0.6510319 -0.752
## x46_13 0.3488158 0.7885792 0.442
## x46_14 0.1356995 1.4717740 0.092
## x46_15 -0.0242932 1.8372890 -0.013
## x46_16 0.6950166 2.2335948 0.311
## x47_2 0.0597098 0.0344372 1.734
## x47_3 -0.0036282 0.0427573 -0.085
## x47_4 -0.0555526 0.0579761 -0.958
## x47_5 0.0461598 0.0755681 0.611
## x47_6 0.1023070 0.1049782 0.975
## x47_7 0.3235190 0.1510130 2.142
## x47_8 -0.0168583 0.2123291 -0.079
## x47_9 -0.0319447 0.2711690 -0.118
## x47_10 0.6338525 0.4771951 1.328
## x47_11 -0.1051888 0.4748226 -0.222
## x47_12 -0.3225899 0.6435940 -0.501
## x47_13 -0.6413051 1.0607703 -0.605
## x47_14 -0.7230154 1.8036665 -0.401
## x47_15 0.8102242 1.8341634 0.442
## x47_16 NA NA NA
## x48_3 -2.7000529 2.2247643 -1.214
## x48_7 -0.7473494 1.2800307 -0.584
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## x52_16 NA NA NA
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## x55_14 1.5898417 1.8192817 0.874
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## x55_16 NA NA NA
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## x58_16 NA NA NA
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## x60_11 0.5631621 1.4935525 0.377
## x60_12 1.5462652 2.5310195 0.611
## x60_13 NA NA NA
## x60_14 NA NA NA
## x60_15 NA NA NA
## x60_16 NA NA NA
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## x63_10 -0.0682142 1.7929899 -0.038
## x63_11 NA NA NA
## x63_12 NA NA NA
## x63_13 NA NA NA
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## x63_16 NA NA NA
## x64_2 -0.0621548 0.1431640 -0.434
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## x64_7 NA NA NA
## x64_8 NA NA NA
## x64_9 NA NA NA
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## x64_11 NA NA NA
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## x64_16 NA NA NA
## x65_2 0.0562533 0.0347152 1.620
## x65_3 0.0806875 0.0435267 1.854
## x65_4 -0.0155950 0.0560623 -0.278
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## x68_16 NA NA NA
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## x69_15 NA NA NA
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## x71_15 NA NA NA
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## x73_16 NA NA NA
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## x76_3 1.8346116 2.0637938 0.889
## x76_4 1.7872265 2.7475443 0.650
## x76_5 NA NA NA
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## x77_5 2.2598267 2.1784753 1.037
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## x81_15 NA NA NA
## x81_16 1.3500681 1.8193604 0.742
## x84_2 NA NA NA
## x84_3 NA NA NA
## x84_4 NA NA NA
## x84_5 NA NA NA
## x84_6 NA NA NA
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## x85_7 NA NA NA
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## x85_14 NA NA NA
## x85_15 NA NA NA
## x85_16 NA NA NA
## x86_2 NA NA NA
## x86_3 0.4803383 1.2932507 0.371
## x86_4 0.4455942 1.2937688 0.344
## x86_5 0.3701466 1.2959099 0.286
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## x86_14 NA NA NA
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## x88_4 NA NA NA
## x88_5 2.8847110 1.8274474 1.579
## x88_6 NA NA NA
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## x88_8 NA NA NA
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## x88_10 NA NA NA
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## x88_12 NA NA NA
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## x88_14 NA NA NA
## x88_16 NA NA NA
## x89_2 0.2694020 0.6751296 0.399
## x89_3 0.4334914 0.6267748 0.692
## x89_4 0.3670938 0.6150989 0.597
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## x96_16 NA NA NA
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## x99_10 0.9160758 1.0528884 0.870
## x99_11 1.0320905 1.0529436 0.980
## x99_12 1.1494944 1.0538781 1.091
## x99_13 1.0164389 1.0561117 0.962
## x99_14 0.9057825 1.0659498 0.850
## x99_15 1.3994017 1.1078415 1.263
## x99_16 0.8014474 1.2039286 0.666
## x102_2 1.7753455 0.7895218 2.249
## x102_3 1.7225255 0.6450625 2.670
## x102_4 1.5898626 0.6184992 2.571
## x102_5 1.1071364 0.6118349 1.810
## x102_6 0.9963167 0.6097832 1.634
## x102_7 0.9764920 0.6093914 1.602
## x102_8 1.0207225 0.6086493 1.677
## x102_9 0.9786532 0.6085768 1.608
## x102_10 0.9603965 0.6090685 1.577
## x102_11 0.9765277 0.6094116 1.602
## x102_12 1.0966049 0.6111668 1.794
## x102_13 1.1399277 0.6168963 1.848
## x102_14 1.1349027 0.6446379 1.761
## x102_15 1.0403004 0.7092564 1.467
## x102_16 1.8770435 1.4552892 1.290
## x103_3 -0.9218646 2.3884752 -0.386
## x103_4 -0.1124236 2.0211313 -0.056
## x103_5 -0.0446460 2.0010421 -0.022
## x103_6 -0.3327679 1.9965456 -0.167
## x103_7 -0.2047399 1.9959522 -0.103
## x103_8 -0.0840480 1.9959848 -0.042
## x103_9 -0.2135074 1.9956503 -0.107
## x103_10 -0.1586986 1.9956897 -0.080
## x103_11 -0.2111897 1.9957427 -0.106
## x103_12 -0.2206405 1.9959993 -0.111
## x103_13 -0.1093563 1.9970417 -0.055
## x103_14 -0.1782277 1.9990502 -0.089
## x103_15 -0.4576738 2.0073012 -0.228
## x103_16 -0.0194410 2.0662427 -0.009
## x104_16 -0.2008361 0.0876038 -2.293
## x106_2 0.0097309 0.0355203 0.274
## x106_3 0.0469103 0.0413963 1.133
## x106_4 -0.0852524 0.0561654 -1.518
## x106_5 0.1132017 0.0788093 1.436
## x106_6 0.2125981 0.1180463 1.801
## x106_7 -0.2537130 0.1937903 -1.309
## x106_8 -0.3880962 0.2349340 -1.652
## x106_9 -0.3003000 0.3613115 -0.831
## x106_10 0.2406168 0.4587803 0.524
## x106_11 -0.3511698 0.7442370 -0.472
## x106_12 8.4104731 0.9204457 9.137
## x106_13 1.3700285 1.1089174 1.235
## x106_14 0.5633189 1.2916101 0.436
## x106_15 NA NA NA
## x106_16 0.3498480 1.3049873 0.268
## Pr(>|t|)
## (Intercept) 0.945634
## x13 < 0.0000000000000002 ***
## x14 0.087605 .
## x18 0.007455 **
## x20 0.526370
## x21 0.243936
## x22 0.300378
## x34 0.010122 *
## x45 < 0.0000000000000002 ***
## x50 0.518783
## x56 0.000000006608621014 ***
## x72 0.152195
## x74 0.209181
## x75 < 0.0000000000000002 ***
## x82 < 0.0000000000000002 ***
## x83 0.000000039295890125 ***
## x90 0.178780
## x92 0.325747
## x94 < 0.0000000000000002 ***
## x101 0.547866
## x105 0.053163 .
## x2_009fdc2d37ffaba8e9854e5bf91e8193 0.002155 **
## x2_0104f035fa3fd6867f97188b1f126c91 0.036950 *
## x2_014498d37e0e50ffbd27edb7b87a02ce 0.003864 **
## x2_01b5b97a96c69e9ee73b325b21a1093e 0.001220 **
## x2_02949cb2e4502b1c382f48731eaa5d7d 0.000082301702896770 ***
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.033631 *
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 0.936721
## x2_03af349e980524ba204e4fdd09583887 0.400501
## x2_03b7592ee764f088fa73a5964181d3eb 0.195605
## x2_03be585b1ec66610133d1e369ea0bae0 0.463046
## x2_044c0dccd777a21ad32dfa271b25b05d 0.084304 .
## x2_04b5a9fbcede6d8da2c9443a74659508 0.921809
## x2_050e1afffbd1d7a2ae2d692e664e8cc6 0.679594
## x2_051d67c71a408ff3d1c5ef12bd4c4beb 0.581894
## x2_0527609acb9d3bb9f16229e4ea213155 0.150750
## x2_053921d1e61fda98664a7cbc984b73bc 0.032882 *
## x2_055310e43ac25f3e7ce8d0197c029b05 0.091355 .
## x2_05d62a51dc2cdb45015ac40846de7d2f 0.526216
## x2_063949e8aa1746c2f2072e3c3dfdf072 0.001973 **
## x2_06970c71617ff7923b250ac7ca9487a4 0.028750 *
## x2_06fee204db920d6132334a5c3022b7f1 0.878792
## x2_087911c45b61db3e68a882004e37718c 0.005689 **
## x2_08858f31ce8691322fa038d8660cf83e 0.859556
## x2_08e6c24b07efe1adef6bb2e463299f2d 0.000002116376023215 ***
## x2_0a28dc4bccab65e38f0c53ba789c83ed 0.518450
## x2_0a69cf48a1af11b4d7a7ef215ffe8622 0.742840
## x2_0a72af1fa112ba359d30fee41d5f93fb 0.101769
## x2_0bc010c231ab369fff9c24dcb493a691 0.340866
## x2_0bda5d7eb1821a2ee9ad763276d4506e 0.540151
## x2_0c9e2bc33a3f374bb3640162acb5d17f 0.099701 .
## x2_0d07f17e244a25eb185c35a74c8933fd 0.219156
## x2_0dc4cab512b3206e5e1bc6cb09979f45 0.977993
## x2_0f485cf337eda5dd5944bec5a0b06ddf 0.002706 **
## x2_0f7c19f51275e21407c8ce1288245eb2 0.872883
## x2_0feb9fe6a7fb9cdb87eb1d9fee3551aa 0.557746
## x2_104bee6dd94618d74bb624495714051f 0.370994
## x2_1075ca3a47325d5f4550b400dd22f7d3 0.849464
## x2_10dcfe9fc130743255177b8ff420e1f9 0.353092
## x2_10f6cfc6ab2a1637ec46f1fe47e40c74 0.016191 *
## x2_113c85f700a5e6e932baeaef711e1d7a 0.020262 *
## x2_123d45ea021f01c2e2375c4b402d8991 0.867453
## x2_1267ff8f4bd26da9b5e5945f806709fd 0.097716 .
## x2_129c5db8146f6531c8be44f5cdfe21e9 0.663960
## x2_12cf91889c40352fdf3ca6e9c4e4675b 0.046592 *
## x2_131f0aac2bba6aa2b94dd9d77d9e25a0 0.816224
## x2_1486a0d04e430836dae79c9059576d1c 0.216819
## x2_14fe7f2dffd4dc845a66707864a7b660 0.010118 *
## x2_153df9695e96a68777e99c67982f5746 0.000019971603568966 ***
## x2_15e8e7d18fb7807216c66cdeb30692e9 0.008504 **
## x2_171cde2526843878887a3223e5b70428 0.295830
## x2_172a0b2b81812459c08365129af5c789 0.643239
## x2_17b6c8d28a9009eb6595627926798a74 0.109950
## x2_17c97746a154d137c62f0160b7f489ab 0.087973 .
## x2_17e1a8e1b27f98989ab96f75a2668a37 0.000007835566895691 ***
## x2_185c423535d71d45e9588031aac9cfa6 0.034418 *
## x2_1920b9287379e68af3d06059beb79e69 0.530530
## x2_192f275f745cabe54420d4e03e682cf8 0.294840
## x2_197201b340da1e659a339b65729783be 0.229284
## x2_1a81ea262fea7bc80844206a444967c8 0.575486
## x2_1a834789d88f232251278c63050fc7cb 0.044881 *
## x2_1af39672631685e6ff064d3abbd88e4c 0.043542 *
## x2_1b09d5cf03fa77d046fccb886172538a 0.631915
## x2_1c3cbc8aadd106d9719117bf1ba46cde 0.908061
## x2_1c4c1b63b9d3f03f2095a8ea32b9b12e 0.534240
## x2_1c5834c38ec7ea30ae8eb4f96c349c3f 0.062944 .
## x2_1d0d7838ce4c6a59c126e70417630238 0.067326 .
## x2_1d38ae60450853859a40fec9ca958611 0.038611 *
## x2_1d4bbcb99529cb99db56adddbef3b1eb 0.846525
## x2_1eae3a63e85686b0287c0bc75b4f7505 0.592611
## x2_1ebc693367872184af173a1f06d4a1e6 0.463375
## x2_1effce387d172a9a92129b9f1fec4841 0.337749
## x2_1fe02ceb59ee78a2fcfd58c59af7e1bf 0.387474
## x2_207d151c484c92186932c013ddca15c9 0.012146 *
## x2_20a2507337678a01558bb346e96230be 0.438896
## x2_20efb04ee762c2f69b47582e66c1c65b 0.020557 *
## x2_210a5a5f6e28f63665233225d386cfc6 0.409775
## x2_213083c1fd2d077ad9ee96f992c28e7b 0.669118
## x2_21f590ffa0c848a6346af02f54cdc4e3 0.813401
## x2_220aac87fa04588c5cc646f89c42aa21 0.796236
## x2_224e87ee9a8e53552f7f73235b0faf5c 0.571535
## x2_2338cc2081828b4ed26e7f37430ae0e0 0.591903
## x2_236a84ed3126415d7bfa0744c7ca3d72 0.497738
## x2_23c3ea3f5fce463108413f9335442fc3 0.510271
## x2_242b432d1edf79dc1c0e73eda036b590 0.008185 **
## x2_24a76d3c6a139c738439aae8caa7be35 0.115079
## x2_24f95a5010da08e96e7aa559a1cfd22d 0.822174
## x2_2536247d525726b531c14e8307612cb6 0.003768 **
## x2_2585ed1efc11aa00042ec30e4c494ba7 0.106491
## x2_2600ab685c2ccb118a862f0b1b0fbfe9 0.149417
## x2_269233ab85f379500360ab847b8d11a4 0.031349 *
## x2_269db099fcbd8d7208fdb4037d494f04 0.057854 .
## x2_27c681dfdc5645ac249a286ff323e199 0.367459
## x2_28091686563aa5bf4f45adeacf5d32d5 0.129565
## x2_29eeae90a43111aded5d4ddfa484b23b 0.082111 .
## x2_2aa97dc7b655139fc9ffce352bd24bb7 0.502296
## x2_2ac9300a0de10e89f00a0e1051e60856 0.793255
## x2_2ad7485f19d0d21d4925dd4d1f61ee99 0.236629
## x2_2b361d80db361c7a17231a1ef2f4c6a4 0.065305 .
## x2_2cc907f118a60f20fc2cc7f76ceab68c 0.814701
## x2_2d0e68fc2b86d6d30e9c58fa3f11ef9a 0.865364
## x2_2d5ba9a7ce396fd5346d904637cc5b0a 0.175956
## x2_2daf09273f61b2b3381d0c70e1b57ec9 0.032602 *
## x2_2df51fa699005c6c64657e84098fd71f 0.891386
## x2_2dfdd7b8b57761e27d9b375c1142cfb2 0.308324
## x2_2eb500524b319bea908cf9560d4769cf 0.608985
## x2_2f0908f9b527b1f5cdfbf6e60d362027 0.045480 *
## x2_2f4a170c729935052b0fda3e3cbe8625 0.318313
## x2_30043a051ec95cdfc753cde5c92deaa0 0.008225 **
## x2_30108c80885d8f9449e3bdd6b6ecd5da 0.174254
## x2_30811f6f82e75fb157e8b93258861b0d 0.000225 ***
## x2_30dd738797f8299c7da368fc95e9eeab 0.013269 *
## x2_30f21b7c216d85b772cc3146d3f9f4d4 0.651474
## x2_3116a5793171246adbf43fe55e4ef2d1 0.381944
## x2_32102a7c9d207b774b08d3195798ce26 0.068437 .
## x2_3355d31b8759d7561093c6f0dfa767db 0.403807
## x2_33616573b4c22e175077dcd1cade96b6 0.015526 *
## x2_33f86129aacde1b8f08541d592d62661 0.007872 **
## x2_34875e7da08b524a0079f442d2059f7c 0.044869 *
## x2_35058dc89e09473f18e9b215d322e144 0.964168
## x2_3509c44a5b1ff31cee9a4878f81c6ecc 0.927403
## x2_350a633119d1a59162b15a33fa0f7861 0.020321 *
## x2_356b8ffa4b7beae198ced54c31e2162d 0.219913
## x2_359df4d63615570eba6759aca0a55226 0.111265
## x2_3623e78af73768e45140372a2ebd4cf1 0.769104
## x2_3673d435b5dd04bf22417eb19cb58c80 0.774342
## x2_367667c7267dbf6425bc6b93a8f73405 0.010875 *
## x2_368863f45545d0ece1402cfac3ff8380 0.937290
## x2_369c07e037bdf9071badfa06c0f6ef4e 0.072153 .
## x2_371ddf3fa48c25be8e3d6d506f1d5906 0.080634 .
## x2_386dc569766aca34389baa6ed194bcab 0.957257
## x2_38c1f83b8003d3e128291b3d7c3a330b 0.042898 *
## x2_38e6c6964bb4152252a85b27d9957da3 0.000633 ***
## x2_38f62052d64569daf6053dab488e3065 0.433422
## x2_397a9138fda0c210d7da5a4a839a3589 0.004068 **
## x2_39c560a0732e0fd890f781f012b23f49 0.571940
## x2_3aa42ca2e840818784f226b985bc9629 0.001923 **
## x2_3aa4c976f41bb60488494c95ed6c6bba 0.500281
## x2_3ab095b5e61de32622e8cce0e611e752 0.106471
## x2_3ad76e9c19ebc9dd18550b64a114b0cd 0.112261
## x2_3af5b01bb233d99a246b53a4e245d94f 0.460538
## x2_3bcd58e81e1e7d093e41ed9193ddfdef 0.274211
## x2_3c9f174cf3f695799cc11998b6936617 0.958635
## x2_3ca53ec023fc382ee041f716fb88d2d0 0.008658 **
## x2_3cb4c46bd235a4e4451b5270b96cfdc1 0.302546
## x2_3d1400872732a97bcab1828ada08f831 0.000358 ***
## x2_3d15540c70bbe48c4098c891ac94d373 0.343653
## x2_3d2bf47c934519d5e2c1ef2895487aca 0.033714 *
## x2_3e1c31c3ff0eb9fbb61ffc7cfa6242f8 0.593100
## x2_3e23bc0253b797991aada73bf356fd39 0.366028
## x2_3e5b5f4ae1b3ea9418ff57ae8e461604 0.063636 .
## x2_3e627d02678fac75b90b71c9bd8c28e4 0.246082
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## x47_12 0.616216
## x47_13 0.545478
## x47_14 0.688531
## x47_15 0.658684
## x47_16 NA
## x48_3 0.224908
## x48_7 0.559329
## x48_8 0.513743
## x48_9 0.680880
## x48_10 0.617068
## x48_11 NA
## x48_13 NA
## x48_14 0.765008
## x48_16 0.870620
## x49_2 0.758737
## x49_3 0.747325
## x49_4 0.745483
## x49_5 0.533114
## x49_6 0.564574
## x49_7 0.540538
## x49_8 0.577681
## x49_9 0.566774
## x49_10 0.568296
## x49_11 0.554895
## x49_12 0.588058
## x49_13 0.591770
## x49_14 0.604816
## x49_15 0.488587
## x49_16 0.593733
## x51_2 0.397286
## x51_3 0.598728
## x51_4 0.428510
## x51_5 0.307420
## x51_6 0.635312
## x51_7 0.584190
## x51_8 0.539174
## x51_9 0.586912
## x51_10 0.544530
## x51_11 0.571677
## x51_12 0.503477
## x51_13 0.498941
## x51_14 0.540982
## x51_15 0.636681
## x51_16 0.146346
## x52_2 0.294800
## x52_3 0.502071
## x52_4 0.663272
## x52_5 0.830047
## x52_6 0.465571
## x52_7 0.231862
## x52_8 0.768071
## x52_9 0.668007
## x52_10 0.541241
## x52_11 0.514970
## x52_12 0.386008
## x52_13 0.569987
## x52_14 0.952843
## x52_16 NA
## x54_2 0.129315
## x54_3 0.146013
## x54_4 0.912139
## x54_5 0.165378
## x54_6 0.000000026698406421 ***
## x54_7 0.000025328473181627 ***
## x54_8 0.001141 **
## x54_9 0.001572 **
## x54_10 0.000076101085600347 ***
## x54_11 0.000023322272943242 ***
## x54_12 0.217635
## x54_13 0.806507
## x54_14 0.647955
## x54_15 0.820553
## x54_16 0.240608
## x55_2 0.096897 .
## x55_3 0.258605
## x55_4 0.324132
## x55_5 0.807671
## x55_6 0.039102 *
## x55_7 0.822543
## x55_8 0.760663
## x55_9 0.636020
## x55_10 0.505379
## x55_11 0.949894
## x55_12 0.823766
## x55_13 0.921217
## x55_14 0.382197
## x55_15 0.922982
## x55_16 NA
## x57_2 0.486314
## x57_3 0.688872
## x57_4 0.906826
## x57_5 0.477602
## x57_6 0.108865
## x57_7 0.477371
## x57_8 0.664117
## x57_9 0.736095
## x57_10 0.528204
## x57_11 0.000056303135727765 ***
## x57_12 0.911138
## x57_13 0.658551
## x57_14 0.298842
## x57_15 0.999516
## x57_16 0.519960
## x58_2 0.328877
## x58_3 0.460380
## x58_4 0.056309 .
## x58_5 0.207281
## x58_6 0.174934
## x58_7 0.182146
## x58_8 0.139753
## x58_9 0.308389
## x58_10 0.472004
## x58_11 0.789764
## x58_12 0.800463
## x58_13 0.758467
## x58_14 0.894848
## x58_15 0.744007
## x58_16 NA
## x60_2 0.841691
## x60_3 0.383651
## x60_4 0.483337
## x60_5 0.526674
## x60_6 0.322680
## x60_7 0.190622
## x60_8 0.067406 .
## x60_9 0.143654
## x60_10 0.959762
## x60_11 0.706133
## x60_12 0.541259
## x60_13 NA
## x60_14 NA
## x60_15 NA
## x60_16 NA
## x61_2 0.787763
## x61_3 0.758534
## x61_4 0.438400
## x61_5 0.309775
## x61_6 0.278906
## x61_7 0.537090
## x61_8 0.578842
## x61_9 0.517166
## x61_10 0.488634
## x61_11 0.506252
## x61_12 0.423657
## x61_13 0.609214
## x61_14 0.554667
## x61_15 0.973852
## x61_16 0.509855
## x63_2 0.018272 *
## x63_3 0.004448 **
## x63_4 0.039923 *
## x63_5 0.019555 *
## x63_6 0.010933 *
## x63_7 0.081848 .
## x63_8 0.139921
## x63_9 0.611408
## x63_10 0.969652
## x63_11 NA
## x63_12 NA
## x63_13 NA
## x63_14 NA
## x63_15 NA
## x63_16 NA
## x64_2 0.664186
## x64_3 0.449797
## x64_4 0.878166
## x64_5 0.945102
## x64_6 0.833615
## x64_7 NA
## x64_8 NA
## x64_9 NA
## x64_10 NA
## x64_11 NA
## x64_12 NA
## x64_14 NA
## x64_16 NA
## x65_2 0.105165
## x65_3 0.063798 .
## x65_4 0.780884
## x65_5 0.339484
## x65_6 0.249682
## x65_7 0.184824
## x65_8 0.000157 ***
## x65_9 0.689964
## x65_10 0.503147
## x65_11 0.000000046231827038 ***
## x65_12 0.137802
## x65_13 0.586112
## x65_14 0.428163
## x65_15 0.221039
## x65_16 0.843468
## x66_7 0.647771
## x66_12 0.939119
## x66_13 0.640879
## x66_14 0.586810
## x66_15 0.861048
## x66_16 NA
## x68_14 0.531721
## x68_15 0.313617
## x68_16 NA
## x69_2 0.388563
## x69_3 0.181115
## x69_4 0.339468
## x69_5 0.339919
## x69_6 0.502771
## x69_7 0.236805
## x69_8 0.307082
## x69_9 0.201270
## x69_10 0.234250
## x69_11 0.116180
## x69_12 0.159474
## x69_13 0.122337
## x69_14 0.341802
## x69_15 NA
## x69_16 0.516559
## x70_2 0.844998
## x70_3 0.818473
## x70_4 0.945476
## x70_16 0.732027
## x71_11 0.545160
## x71_12 0.620220
## x71_13 0.611737
## x71_14 0.606210
## x71_15 NA
## x71_16 0.938852
## x73_2 0.469410
## x73_3 0.245146
## x73_4 0.461475
## x73_5 0.315729
## x73_6 0.310285
## x73_7 0.697601
## x73_8 0.609376
## x73_9 0.186237
## x73_10 0.804985
## x73_11 0.222853
## x73_12 0.516000
## x73_13 0.113037
## x73_14 0.610242
## x73_15 0.000285 ***
## x73_16 NA
## x76_2 0.846638
## x76_3 0.374045
## x76_4 0.515393
## x76_5 NA
## x76_6 NA
## x76_7 NA
## x76_8 NA
## x76_9 NA
## x76_10 NA
## x76_11 NA
## x76_12 NA
## x76_13 NA
## x76_14 NA
## x76_15 NA
## x76_16 NA
## x77_3 NA
## x77_5 0.299595
## x77_6 0.692926
## x77_16 NA
## x79_2 0.429624
## x79_3 0.256378
## x79_4 0.221538
## x79_5 0.203292
## x79_6 0.089355 .
## x79_7 0.098892 .
## x79_8 0.112266
## x79_9 0.119000
## x79_10 0.120330
## x79_11 0.117157
## x79_12 0.108144
## x79_13 0.181645
## x79_14 0.259318
## x79_15 0.120607
## x79_16 0.532308
## x80_10 0.612670
## x80_11 0.631601
## x80_12 0.485568
## x80_16 0.766741
## x81_2 0.657711
## x81_3 0.674546
## x81_4 0.585643
## x81_5 0.637312
## x81_6 0.425814
## x81_7 0.256826
## x81_8 0.000000000000000794 ***
## x81_9 0.000000091963104216 ***
## x81_10 0.543664
## x81_11 0.775677
## x81_12 0.508782
## x81_13 0.083515 .
## x81_15 NA
## x81_16 0.458066
## x84_2 NA
## x84_3 NA
## x84_4 NA
## x84_5 NA
## x84_6 NA
## x84_7 NA
## x84_8 NA
## x84_9 NA
## x84_10 NA
## x84_11 NA
## x84_12 NA
## x84_13 NA
## x84_14 NA
## x84_15 NA
## x84_16 NA
## x85_7 NA
## x85_12 NA
## x85_13 NA
## x85_14 NA
## x85_15 NA
## x85_16 NA
## x86_2 NA
## x86_3 0.710331
## x86_4 0.730539
## x86_5 0.775168
## x86_6 0.874295
## x86_7 0.448874
## x86_11 0.955732
## x86_14 NA
## x86_16 0.528375
## x87_2 0.635003
## x87_3 0.723158
## x87_4 0.861928
## x87_5 0.842873
## x87_6 0.831239
## x87_7 0.718581
## x87_8 0.845978
## x87_9 0.981829
## x87_10 0.889693
## x87_11 0.774013
## x87_12 0.824487
## x87_13 0.869149
## x87_14 0.855967
## x87_15 0.578314
## x87_16 0.691896
## x88_2 0.836229
## x88_3 0.706590
## x88_4 NA
## x88_5 0.114464
## x88_6 NA
## x88_7 0.688597
## x88_8 NA
## x88_9 NA
## x88_10 NA
## x88_11 NA
## x88_12 NA
## x88_13 NA
## x88_14 NA
## x88_16 NA
## x89_2 0.689872
## x89_3 0.489187
## x89_4 0.550648
## x89_5 0.414963
## x89_6 0.430410
## x89_7 0.428855
## x89_8 0.528182
## x89_9 0.490966
## x89_10 0.537378
## x89_11 0.414479
## x89_12 0.527509
## x89_13 0.595387
## x89_14 0.192228
## x89_15 0.462155
## x89_16 0.729564
## x93_2 0.162433
## x93_3 0.413308
## x93_4 0.351052
## x93_5 0.441372
## x93_6 0.447445
## x93_7 0.557049
## x93_8 0.541965
## x93_9 0.481760
## x93_10 0.434290
## x93_11 0.462337
## x93_12 0.478615
## x93_13 0.391718
## x93_14 0.447240
## x93_15 0.556250
## x93_16 0.000004484686413874 ***
## x95_2 0.075137 .
## x95_3 0.066406 .
## x95_4 0.167781
## x95_5 0.382135
## x95_6 0.443557
## x95_7 0.386047
## x95_8 0.406859
## x95_9 0.411680
## x95_10 0.413955
## x95_11 0.506187
## x95_12 0.541967
## x95_13 0.541783
## x95_14 0.467705
## x95_15 0.470793
## x95_16 0.369884
## x96_2 0.830756
## x96_3 0.520002
## x96_4 0.817598
## x96_5 0.697099
## x96_6 0.549613
## x96_7 0.512534
## x96_8 0.957374
## x96_9 0.226851
## x96_10 0.471944
## x96_11 0.086932 .
## x96_12 0.150104
## x96_13 0.000000732382973751 ***
## x96_14 0.196223
## x96_15 0.388731
## x96_16 NA
## x97_16 0.415238
## x98_2 0.473654
## x98_3 0.334290
## x98_4 0.491741
## x98_5 0.358672
## x98_6 0.404375
## x98_7 0.334109
## x98_8 0.364387
## x98_9 0.356945
## x98_10 0.327340
## x98_11 0.330030
## x98_12 0.213202
## x98_13 0.192368
## x98_14 0.127280
## x98_15 0.175928
## x98_16 0.243832
## x99_2 0.259065
## x99_3 0.419450
## x99_4 0.539912
## x99_5 0.389141
## x99_6 0.389712
## x99_7 0.415066
## x99_8 0.388096
## x99_9 0.418362
## x99_10 0.384283
## x99_11 0.327007
## x99_12 0.275412
## x99_13 0.335849
## x99_14 0.395484
## x99_15 0.206547
## x99_16 0.505619
## x102_2 0.024552 *
## x102_3 0.007587 **
## x102_4 0.010165 *
## x102_5 0.070391 .
## x102_6 0.102306
## x102_7 0.109090
## x102_8 0.093560 .
## x102_9 0.107837
## x102_10 0.114859
## x102_11 0.109089
## x102_12 0.072791 .
## x102_13 0.064647 .
## x102_14 0.078341 .
## x102_15 0.142468
## x102_16 0.197140
## x103_3 0.699530
## x103_4 0.955642
## x103_5 0.982200
## x103_6 0.867631
## x103_7 0.918300
## x103_8 0.966413
## x103_9 0.914801
## x103_10 0.936620
## x103_11 0.915727
## x103_12 0.911982
## x103_13 0.956331
## x103_14 0.928959
## x103_15 0.819646
## x103_16 0.992493
## x104_16 0.021889 *
## x106_2 0.784125
## x106_3 0.257151
## x106_4 0.129068
## x106_5 0.150912
## x106_6 0.071730 .
## x106_7 0.190484
## x106_8 0.098571 .
## x106_9 0.405910
## x106_10 0.599960
## x106_11 0.637040
## x106_12 < 0.0000000000000002 ***
## x106_13 0.216679
## x106_14 0.662744
## x106_15 NA
## x106_16 0.788638
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 1.605 on 13310 degrees of freedom
## Multiple R-squared: 0.6035, Adjusted R-squared: 0.4792
## F-statistic: 4.855 on 4172 and 13310 DF, p-value: < 0.00000000000000022novo_TrainSet <- TrainSet
novo_ValidSet <- ValidSet
novo_modelo <- modelo_inicialCalculando os resíduos padronizados do modelo
novo_TrainSet$Val_pred <- predict(novo_modelo)
novo_TrainSet$residuo <- resid(novo_modelo)
novo_TrainSet$rp <- rstandard(novo_modelo)k) Calcular as medidas de erros do modelo na amostra train.csv.
Erro quadratico medio na amostra de treino
mse <- mean((novo_TrainSet$target - novo_TrainSet$Val_pred)^2)
sqrt(mse)## [1] 1.400736j) Análise de resíduos
plot(predict(novo_modelo),novo_TrainSet$residuo, xlab = "Preditor linear",ylab = "Residuos")
abline(h = 0, lty = 2)
qqnorm(residuals(novo_modelo), ylab="Residuos",xlab="Quantis teoricos",main="")
qqline(residuals(novo_modelo))
Excluindo os outliers
#Excluir os outliers
TrainSet_1 <-filter(novo_TrainSet,novo_TrainSet$rp>=-2&novo_TrainSet$rp<=2)
#Pre-processamento dos dados
# Apaga a coluna
TrainSet_1$Val_pred = NULL
TrainSet_1$residuo = NULL
TrainSet_1$rp = NULLRe-treino do modelo1 sem os outliers
modelo1 <- lm(target ~ ., data = TrainSet_1)
summary(modelo1)##
## Call:
## lm(formula = target ~ ., data = TrainSet_1)
##
## Residuals:
## Min 1Q Median 3Q Max
## -2.5015 -0.4934 -0.0622 0.3898 4.3753
##
## Coefficients: (142 not defined because of singularities)
## Estimate Std. Error t value
## (Intercept) 2.10229092 3.64406388 0.577
## x13 -0.36165341 0.02664129 -13.575
## x14 0.18755767 0.06410298 2.926
## x18 0.52923048 0.12722259 4.160
## x20 -34.42832608 20.68122158 -1.665
## x21 -0.10303073 0.03348217 -3.077
## x22 1.75263457 1.01090742 1.734
## x34 0.14649897 0.03221607 4.547
## x45 -0.78360184 0.02664911 -29.404
## x50 -0.07805031 0.48572780 -0.161
## x56 0.20439355 0.02366833 8.636
## x72 0.07170751 0.02687285 2.668
## x74 -0.05787949 0.02663432 -2.173
## x75 -0.64535134 0.02197645 -29.366
## x82 -0.64934577 0.02670010 -24.320
## x83 0.20520896 0.02690807 7.626
## x90 -0.34039777 0.44992322 -0.757
## x92 -1.76221801 1.07431109 -1.640
## x94 0.83485020 0.02682416 31.123
## x101 33.36701999 20.60707612 1.619
## x105 0.40394332 0.17257608 2.341
## x2_009fdc2d37ffaba8e9854e5bf91e8193 1.28718465 0.24909155 5.168
## x2_0104f035fa3fd6867f97188b1f126c91 0.73446567 0.25445228 2.886
## x2_014498d37e0e50ffbd27edb7b87a02ce 1.01246855 0.24884088 4.069
## x2_01b5b97a96c69e9ee73b325b21a1093e 0.96417991 0.25322812 3.808
## x2_02949cb2e4502b1c382f48731eaa5d7d 1.71653653 0.26760596 6.414
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.50012404 0.25748378 1.942
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 -0.13046317 0.26086211 -0.500
## x2_03af349e980524ba204e4fdd09583887 -0.18174478 0.26395395 -0.689
## x2_03b7592ee764f088fa73a5964181d3eb 0.55296079 0.27148698 2.037
## x2_03be585b1ec66610133d1e369ea0bae0 0.51782282 0.24034756 2.154
## x2_044c0dccd777a21ad32dfa271b25b05d -0.46404113 0.25137188 -1.846
## x2_04b5a9fbcede6d8da2c9443a74659508 -0.00581490 0.27247401 -0.021
## x2_050e1afffbd1d7a2ae2d692e664e8cc6 -0.03918104 0.23413315 -0.167
## x2_051d67c71a408ff3d1c5ef12bd4c4beb -0.20442499 0.25099170 -0.814
## x2_0527609acb9d3bb9f16229e4ea213155 0.76824976 0.25463562 3.017
## x2_053921d1e61fda98664a7cbc984b73bc 0.61724069 0.24912743 2.478
## x2_055310e43ac25f3e7ce8d0197c029b05 0.82137395 0.29291855 2.804
## x2_05d62a51dc2cdb45015ac40846de7d2f -0.25330338 0.23823956 -1.063
## x2_063949e8aa1746c2f2072e3c3dfdf072 0.69946923 0.27731596 2.522
## x2_06970c71617ff7923b250ac7ca9487a4 0.72108703 0.23921226 3.014
## x2_06fee204db920d6132334a5c3022b7f1 0.29142305 0.24644350 1.183
## x2_087911c45b61db3e68a882004e37718c 1.07702734 0.26268134 4.100
## x2_08858f31ce8691322fa038d8660cf83e 0.24634636 0.25254918 0.975
## x2_08e6c24b07efe1adef6bb2e463299f2d 1.03716618 0.31001367 3.346
## x2_0a28dc4bccab65e38f0c53ba789c83ed -0.21446059 0.24098802 -0.890
## x2_0a69cf48a1af11b4d7a7ef215ffe8622 0.05209911 0.24967716 0.209
## x2_0a72af1fa112ba359d30fee41d5f93fb -0.35150331 0.23909252 -1.470
## x2_0bc010c231ab369fff9c24dcb493a691 -0.34638727 0.30475616 -1.137
## x2_0bda5d7eb1821a2ee9ad763276d4506e -0.14085769 0.24869917 -0.566
## x2_0c9e2bc33a3f374bb3640162acb5d17f -0.46224361 0.26048113 -1.775
## x2_0d07f17e244a25eb185c35a74c8933fd -0.49083993 0.27681974 -1.773
## x2_0dc4cab512b3206e5e1bc6cb09979f45 0.14864390 0.23717790 0.627
## x2_0f485cf337eda5dd5944bec5a0b06ddf 0.86704593 0.24350075 3.561
## x2_0f7c19f51275e21407c8ce1288245eb2 0.11860072 0.25798877 0.460
## x2_0feb9fe6a7fb9cdb87eb1d9fee3551aa -0.30884583 0.25543464 -1.209
## x2_104bee6dd94618d74bb624495714051f 0.47673535 0.25032904 1.904
## x2_1075ca3a47325d5f4550b400dd22f7d3 -0.05651722 0.23614660 -0.239
## x2_10dcfe9fc130743255177b8ff420e1f9 -0.15488012 0.23821012 -0.650
## x2_10f6cfc6ab2a1637ec46f1fe47e40c74 0.64609775 0.27404359 2.358
## x2_113c85f700a5e6e932baeaef711e1d7a 1.08008256 0.25131453 4.298
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## x1_15 NA NA NA
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## x6_13 NA NA NA
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## x6_15 NA NA NA
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## x7_2 0.24160249 0.71204803 0.339
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## x8_16 NA NA NA
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## x9_7 0.00320035 0.99608403 0.003
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## x9_16 NA NA NA
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## x11_12 NA NA NA
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## x29_8 NA NA NA
## x29_9 NA NA NA
## x29_10 NA NA NA
## x29_11 NA NA NA
## x29_12 NA NA NA
## x29_14 NA NA NA
## x29_16 NA NA NA
## x30_2 0.31989096 0.53313785 0.600
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## x35_7 NA NA NA
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## x40_2 1.83999294 1.04164768 1.766
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## x40_5 1.25981577 0.99152264 1.271
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## x40_8 1.45640132 0.99086032 1.470
## x40_9 1.47926768 0.99090224 1.493
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## x40_12 1.83669196 0.99214626 1.851
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## x42_15 NA NA NA
## x42_16 NA NA NA
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## x43_16 NA NA NA
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## x46_16 NA NA NA
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## x47_14 NA NA NA
## x47_15 NA NA NA
## x47_16 NA NA NA
## x48_3 NA NA NA
## x48_7 0.29686205 0.69940873 0.424
## x48_8 0.44848835 0.71821764 0.624
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## x48_11 NA NA NA
## x48_13 NA NA NA
## x48_14 NA NA NA
## x48_16 NA NA NA
## x49_2 0.07373722 0.55499588 0.133
## x49_3 0.28271848 0.51465052 0.549
## x49_4 0.17138216 0.50275977 0.341
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## x52_13 -0.15705961 0.60409040 -0.260
## x52_14 0.80597695 0.70272095 1.147
## x52_16 NA NA NA
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## x54_14 0.56157267 0.71282222 0.788
## x54_15 NA NA NA
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## x55_14 NA NA NA
## x55_15 -0.47896079 0.99127467 -0.483
## x55_16 NA NA NA
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## x57_15 2.05666613 0.71306016 2.884
## x57_16 1.07399145 0.71403760 1.504
## x58_2 NA NA NA
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## x58_4 0.48095741 0.33232969 1.447
## x58_5 0.48453888 0.25022360 1.936
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## x58_16 NA NA NA
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## x60_12 NA NA NA
## x60_13 NA NA NA
## x60_14 NA NA NA
## x60_15 NA NA NA
## x60_16 NA NA NA
## x61_2 -0.37379422 0.50432329 -0.741
## x61_3 -0.84760931 0.47203567 -1.796
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## x63_10 -1.98402124 0.98599871 -2.012
## x63_11 NA NA NA
## x63_12 NA NA NA
## x63_13 NA NA NA
## x63_14 NA NA NA
## x63_15 NA NA NA
## x63_16 NA NA NA
## x64_2 -0.01290776 0.07902311 -0.163
## x64_3 0.11280229 0.21808129 0.517
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## x64_7 NA NA NA
## x64_8 NA NA NA
## x64_9 NA NA NA
## x64_10 NA NA NA
## x64_11 NA NA NA
## x64_12 NA NA NA
## x64_14 NA NA NA
## x64_16 NA NA NA
## x65_2 0.07011554 0.01922842 3.646
## x65_3 0.06020247 0.02417003 2.491
## x65_4 0.00890479 0.03099978 0.287
## x65_5 0.08067657 0.03977305 2.028
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## x65_8 0.24966658 0.10063145 2.481
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## x65_13 -0.00959128 0.44742085 -0.021
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## x65_15 NA NA NA
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## x66_7 1.18826422 1.18120023 1.006
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## x66_16 NA NA NA
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## x68_16 NA NA NA
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## x69_3 0.18822668 0.32193611 0.585
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## x69_15 NA NA NA
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## x70_3 1.26659251 0.98725429 1.283
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## x70_16 NA NA NA
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## x76_4 NA NA NA
## x76_5 NA NA NA
## x76_6 NA NA NA
## x76_7 NA NA NA
## x76_8 NA NA NA
## x76_9 NA NA NA
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## x76_11 NA NA NA
## x76_12 NA NA NA
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## x76_15 NA NA NA
## x76_16 NA NA NA
## x77_3 NA NA NA
## x77_5 1.41838818 0.62383914 2.274
## x77_6 NA NA NA
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## x81_12 -0.09198549 0.46146602 -0.199
## x81_13 0.53721104 0.71003435 0.757
## x81_15 NA NA NA
## x81_16 NA NA NA
## x84_2 NA NA NA
## x84_3 NA NA NA
## x84_4 NA NA NA
## x84_5 NA NA NA
## x84_6 NA NA NA
## x84_7 NA NA NA
## x84_8 NA NA NA
## x84_9 NA NA NA
## x84_10 NA NA NA
## x84_11 NA NA NA
## x84_12 NA NA NA
## x84_13 NA NA NA
## x84_14 NA NA NA
## x84_15 NA NA NA
## x84_16 NA NA NA
## x85_7 NA NA NA
## x85_12 NA NA NA
## x85_13 NA NA NA
## x85_14 NA NA NA
## x85_15 NA NA NA
## x85_16 NA NA NA
## x86_2 NA NA NA
## x86_3 0.65752793 0.70656507 0.931
## x86_4 0.61914779 0.70687776 0.876
## x86_5 0.56238249 0.70803702 0.794
## x86_6 0.64501666 0.91463633 0.705
## x86_7 NA NA NA
## x86_11 NA NA NA
## x86_14 NA NA NA
## x86_16 NA NA NA
## x87_2 0.79133792 1.03454627 0.765
## x87_3 0.51236382 1.02352780 0.501
## x87_4 0.23984744 1.01943100 0.235
## x87_5 0.32534540 1.01875659 0.319
## x87_6 0.23753546 1.01829247 0.233
## x87_7 0.44319827 1.01811003 0.435
## x87_8 0.25987717 1.01820505 0.255
## x87_9 0.05467954 1.01814189 0.054
## x87_10 -0.01455151 1.01823818 -0.014
## x87_11 -0.14810832 1.01830475 -0.145
## x87_12 -0.10052606 1.01857185 -0.099
## x87_13 -0.00614493 1.01925605 -0.006
## x87_14 -0.02600216 1.02453062 -0.025
## x87_15 -0.01056123 1.04144177 -0.010
## x87_16 -0.07356508 1.08593954 -0.068
## x88_2 -0.18855630 0.24286597 -0.776
## x88_3 -0.42478272 0.47739838 -0.890
## x88_4 NA NA NA
## x88_5 1.71460618 0.99838231 1.717
## x88_6 NA NA NA
## x88_7 -1.08404756 0.99805284 -1.086
## x88_8 NA NA NA
## x88_9 NA NA NA
## x88_10 NA NA NA
## x88_11 NA NA NA
## x88_12 NA NA NA
## x88_13 NA NA NA
## x88_14 NA NA NA
## x88_16 NA NA NA
## x89_2 -0.15089208 0.36918875 -0.409
## x89_3 0.01435974 0.34240826 0.042
## x89_4 -0.02886712 0.33593614 -0.086
## x89_5 0.03513996 0.33404369 0.105
## x89_6 -0.01414722 0.33339669 -0.042
## x89_7 -0.05144816 0.33307836 -0.154
## x89_8 -0.12329088 0.33323077 -0.370
## x89_9 -0.05879403 0.33314839 -0.176
## x89_10 -0.09644527 0.33322933 -0.289
## x89_11 -0.03247622 0.33386018 -0.097
## x89_12 -0.11539712 0.33542646 -0.344
## x89_13 -0.15244740 0.33993069 -0.448
## x89_14 -0.09475970 0.36294520 -0.261
## x89_15 -0.08480330 0.42073612 -0.202
## x89_16 -0.19686508 0.55576016 -0.354
## x93_2 1.22543041 0.63333891 1.935
## x93_3 0.11752783 0.58721587 0.200
## x93_4 0.01822013 0.57440754 0.032
## x93_5 0.01623172 0.56796916 0.029
## x93_6 0.00196282 0.56791498 0.003
## x93_7 -0.15136638 0.56825749 -0.266
## x93_8 -0.11426110 0.56835043 -0.201
## x93_9 -0.09609343 0.56830394 -0.169
## x93_10 -0.02124042 0.56860600 -0.037
## x93_11 0.01651496 0.56874235 0.029
## x93_12 -0.02076989 0.57043936 -0.036
## x93_13 0.05949023 0.57323660 0.104
## x93_14 0.08704084 0.58423256 0.149
## x93_15 -0.11457296 0.63658694 -0.180
## x93_16 NA NA NA
## x95_2 1.21664838 0.74387925 1.636
## x95_3 0.90285318 0.71127009 1.269
## x95_4 0.53631509 0.70547721 0.760
## x95_5 0.17656814 0.70296975 0.251
## x95_6 0.08153761 0.70246915 0.116
## x95_7 0.12061039 0.70231876 0.172
## x95_8 0.10456068 0.70220738 0.149
## x95_9 0.09409365 0.70216104 0.134
## x95_10 0.13988957 0.70198202 0.199
## x95_11 0.01696241 0.70204193 0.024
## x95_12 -0.07200746 0.70208349 -0.103
## x95_13 -0.06330283 0.70260550 -0.090
## x95_14 -0.02311909 0.70370538 -0.033
## x95_15 -0.11669306 0.70881811 -0.165
## x95_16 -0.18074835 0.75989033 -0.238
## x96_2 -0.02015413 0.06248262 -0.323
## x96_3 0.07908354 0.06850728 1.154
## x96_4 -0.00383089 0.08111635 -0.047
## x96_5 0.05743179 0.09716834 0.591
## x96_6 0.00685731 0.11655744 0.059
## x96_7 0.04892688 0.13994947 0.350
## x96_8 0.03482503 0.17261209 0.202
## x96_9 0.13485515 0.21271119 0.634
## x96_10 0.42430500 0.28423243 1.493
## x96_11 0.29825501 0.34112138 0.874
## x96_12 0.63108805 0.43371040 1.455
## x96_13 1.98543539 0.87934056 2.258
## x96_14 1.42507720 0.96834030 1.472
## x96_15 NA NA NA
## x96_16 NA NA NA
## x97_16 -0.05070033 0.04067610 -1.246
## x98_2 0.42154449 0.50613123 0.833
## x98_3 0.43309607 0.47252935 0.917
## x98_4 0.48512370 0.45732760 1.061
## x98_5 0.30974476 0.45097737 0.687
## x98_6 0.35975935 0.44836149 0.802
## x98_7 0.35433237 0.44751619 0.792
## x98_8 0.35110632 0.44666990 0.786
## x98_9 0.35455588 0.44627691 0.794
## x98_10 0.35110182 0.44625119 0.787
## x98_11 0.34513505 0.44627158 0.773
## x98_12 0.57044004 0.44631776 1.278
## x98_13 0.62692993 0.44639914 1.404
## x98_14 0.67459991 0.44713654 1.509
## x98_15 0.55608536 0.45108393 1.233
## x98_16 0.78484951 0.47758018 1.643
## x99_2 -0.11450141 0.64409572 -0.178
## x99_3 0.11298444 0.58602321 0.193
## x99_4 0.01905909 0.57844725 0.033
## x99_5 0.11791212 0.57602437 0.205
## x99_6 0.13605325 0.57507553 0.237
## x99_7 0.12264076 0.57477515 0.213
## x99_8 0.13096199 0.57481926 0.228
## x99_9 0.11362089 0.57479755 0.198
## x99_10 0.13631593 0.57499479 0.237
## x99_11 0.21686534 0.57501860 0.377
## x99_12 0.28841030 0.57554240 0.501
## x99_13 0.21092949 0.57682724 0.366
## x99_14 0.24138700 0.58217868 0.415
## x99_15 0.66938990 0.60670370 1.103
## x99_16 0.21393637 0.65736636 0.325
## x102_2 1.20379681 0.43186542 2.787
## x102_3 0.66197523 0.35456609 1.867
## x102_4 0.62056587 0.33861938 1.833
## x102_5 0.19375546 0.33479754 0.579
## x102_6 0.15471334 0.33371710 0.464
## x102_7 0.17416147 0.33344376 0.522
## x102_8 0.21836086 0.33306331 0.656
## x102_9 0.18426291 0.33301181 0.553
## x102_10 0.18124710 0.33327122 0.544
## x102_11 0.15632347 0.33345801 0.469
## x102_12 0.32666043 0.33451750 0.977
## x102_13 0.34860892 0.33761795 1.033
## x102_14 0.42117146 0.35337560 1.192
## x102_15 0.38242026 0.38789093 0.986
## x102_16 0.60475313 0.79486839 0.761
## x103_3 -0.59279207 0.77839944 -0.762
## x103_4 0.21860557 0.34832040 0.628
## x103_5 0.13834030 0.31112012 0.445
## x103_6 -0.04533074 0.30372043 -0.149
## x103_7 0.04989497 0.30184270 0.165
## x103_8 0.07696094 0.30131156 0.255
## x103_9 0.03849240 0.30104615 0.128
## x103_10 0.05707134 0.30112161 0.190
## x103_11 0.03063640 0.30124071 0.102
## x103_12 0.06891995 0.30166508 0.228
## x103_13 0.08991216 0.30331514 0.296
## x103_14 0.10457284 0.30726988 0.340
## x103_15 -0.21718792 0.32612767 -0.666
## x103_16 NA NA NA
## x104_16 -0.15810533 0.04891142 -3.232
## x106_2 0.02222541 0.01967725 1.129
## x106_3 0.03564188 0.02296367 1.552
## x106_4 -0.04200613 0.03119431 -1.347
## x106_5 -0.00955867 0.04380459 -0.218
## x106_6 0.17716796 0.06540792 2.709
## x106_7 -0.15727076 0.10683760 -1.472
## x106_8 -0.13204084 0.12852102 -1.027
## x106_9 -0.13982735 0.19745100 -0.708
## x106_10 0.42738940 0.25066012 1.705
## x106_11 -0.34682905 0.40665812 -0.853
## x106_12 NA NA NA
## x106_13 1.05914249 0.60546332 1.749
## x106_14 1.02096814 0.70602948 1.446
## x106_15 NA NA NA
## x106_16 0.00027375 0.71325315 0.000
## Pr(>|t|)
## (Intercept) 0.564011
## x13 < 0.0000000000000002 ***
## x14 0.003441 **
## x18 0.0000320491345581 ***
## x20 0.095994 .
## x21 0.002094 **
## x22 0.082991 .
## x34 0.0000054813287059 ***
## x45 < 0.0000000000000002 ***
## x50 0.872342
## x56 < 0.0000000000000002 ***
## x72 0.007631 **
## x74 0.029790 *
## x75 < 0.0000000000000002 ***
## x82 < 0.0000000000000002 ***
## x83 0.0000000000000259 ***
## x90 0.449322
## x92 0.100962
## x94 < 0.0000000000000002 ***
## x101 0.105428
## x105 0.019265 *
## x2_009fdc2d37ffaba8e9854e5bf91e8193 0.0000002407875913 ***
## x2_0104f035fa3fd6867f97188b1f126c91 0.003903 **
## x2_014498d37e0e50ffbd27edb7b87a02ce 0.0000475513204810 ***
## x2_01b5b97a96c69e9ee73b325b21a1093e 0.000141 ***
## x2_02949cb2e4502b1c382f48731eaa5d7d 0.0000000001463260 ***
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.052116 .
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 0.616997
## x2_03af349e980524ba204e4fdd09583887 0.491121
## x2_03b7592ee764f088fa73a5964181d3eb 0.041692 *
## x2_03be585b1ec66610133d1e369ea0bae0 0.031222 *
## x2_044c0dccd777a21ad32dfa271b25b05d 0.064910 .
## x2_04b5a9fbcede6d8da2c9443a74659508 0.982974
## x2_050e1afffbd1d7a2ae2d692e664e8cc6 0.867101
## x2_051d67c71a408ff3d1c5ef12bd4c4beb 0.415391
## x2_0527609acb9d3bb9f16229e4ea213155 0.002557 **
## x2_053921d1e61fda98664a7cbc984b73bc 0.013239 *
## x2_055310e43ac25f3e7ce8d0197c029b05 0.005053 **
## x2_05d62a51dc2cdb45015ac40846de7d2f 0.287698
## x2_063949e8aa1746c2f2072e3c3dfdf072 0.011672 *
## x2_06970c71617ff7923b250ac7ca9487a4 0.002580 **
## x2_06fee204db920d6132334a5c3022b7f1 0.237023
## x2_087911c45b61db3e68a882004e37718c 0.0000415465758365 ***
## x2_08858f31ce8691322fa038d8660cf83e 0.329361
## x2_08e6c24b07efe1adef6bb2e463299f2d 0.000824 ***
## x2_0a28dc4bccab65e38f0c53ba789c83ed 0.373524
## x2_0a69cf48a1af11b4d7a7ef215ffe8622 0.834712
## x2_0a72af1fa112ba359d30fee41d5f93fb 0.141544
## x2_0bc010c231ab369fff9c24dcb493a691 0.255725
## x2_0bda5d7eb1821a2ee9ad763276d4506e 0.571147
## x2_0c9e2bc33a3f374bb3640162acb5d17f 0.075992 .
## x2_0d07f17e244a25eb185c35a74c8933fd 0.076229 .
## x2_0dc4cab512b3206e5e1bc6cb09979f45 0.530855
## x2_0f485cf337eda5dd5944bec5a0b06ddf 0.000371 ***
## x2_0f7c19f51275e21407c8ce1288245eb2 0.645730
## x2_0feb9fe6a7fb9cdb87eb1d9fee3551aa 0.226647
## x2_104bee6dd94618d74bb624495714051f 0.056876 .
## x2_1075ca3a47325d5f4550b400dd22f7d3 0.810853
## x2_10dcfe9fc130743255177b8ff420e1f9 0.515586
## x2_10f6cfc6ab2a1637ec46f1fe47e40c74 0.018406 *
## x2_113c85f700a5e6e932baeaef711e1d7a 0.0000173827430135 ***
## x2_123d45ea021f01c2e2375c4b402d8991 0.710082
## x2_1267ff8f4bd26da9b5e5945f806709fd 0.0000487920939124 ***
## x2_129c5db8146f6531c8be44f5cdfe21e9 0.648493
## x2_12cf91889c40352fdf3ca6e9c4e4675b 0.0000893267358714 ***
## x2_131f0aac2bba6aa2b94dd9d77d9e25a0 0.736316
## x2_1486a0d04e430836dae79c9059576d1c 0.004062 **
## x2_14fe7f2dffd4dc845a66707864a7b660 0.001823 **
## x2_153df9695e96a68777e99c67982f5746 0.0000815767597322 ***
## x2_15e8e7d18fb7807216c66cdeb30692e9 0.0000000208803317 ***
## x2_171cde2526843878887a3223e5b70428 0.196440
## x2_172a0b2b81812459c08365129af5c789 0.513567
## x2_17b6c8d28a9009eb6595627926798a74 0.007423 **
## x2_17c97746a154d137c62f0160b7f489ab 0.004402 **
## x2_17e1a8e1b27f98989ab96f75a2668a37 0.001698 **
## x2_185c423535d71d45e9588031aac9cfa6 0.019369 *
## x2_1920b9287379e68af3d06059beb79e69 0.208099
## x2_192f275f745cabe54420d4e03e682cf8 0.327615
## x2_197201b340da1e659a339b65729783be 0.392080
## x2_1a81ea262fea7bc80844206a444967c8 0.209929
## x2_1a834789d88f232251278c63050fc7cb 0.061597 .
## x2_1af39672631685e6ff064d3abbd88e4c 0.000612 ***
## x2_1b09d5cf03fa77d046fccb886172538a 0.290988
## x2_1c3cbc8aadd106d9719117bf1ba46cde 0.773733
## x2_1c4c1b63b9d3f03f2095a8ea32b9b12e 0.260008
## x2_1c5834c38ec7ea30ae8eb4f96c349c3f 0.110428
## x2_1d0d7838ce4c6a59c126e70417630238 0.004349 **
## x2_1d38ae60450853859a40fec9ca958611 0.085954 .
## x2_1d4bbcb99529cb99db56adddbef3b1eb 0.986939
## x2_1eae3a63e85686b0287c0bc75b4f7505 0.781572
## x2_1ebc693367872184af173a1f06d4a1e6 0.694082
## x2_1effce387d172a9a92129b9f1fec4841 0.317587
## x2_1fe02ceb59ee78a2fcfd58c59af7e1bf 0.350888
## x2_207d151c484c92186932c013ddca15c9 0.0000028151592927 ***
## x2_20a2507337678a01558bb346e96230be 0.359542
## x2_20efb04ee762c2f69b47582e66c1c65b 0.003091 **
## x2_210a5a5f6e28f63665233225d386cfc6 0.120459
## x2_213083c1fd2d077ad9ee96f992c28e7b 0.565044
## x2_21f590ffa0c848a6346af02f54cdc4e3 0.987667
## x2_220aac87fa04588c5cc646f89c42aa21 0.797542
## x2_224e87ee9a8e53552f7f73235b0faf5c 0.316478
## x2_2338cc2081828b4ed26e7f37430ae0e0 0.933474
## x2_236a84ed3126415d7bfa0744c7ca3d72 0.381974
## x2_23c3ea3f5fce463108413f9335442fc3 0.276393
## x2_242b432d1edf79dc1c0e73eda036b590 0.0000889137283965 ***
## x2_24a76d3c6a139c738439aae8caa7be35 0.000216 ***
## x2_24f95a5010da08e96e7aa559a1cfd22d 0.735246
## x2_2536247d525726b531c14e8307612cb6 0.000359 ***
## x2_2585ed1efc11aa00042ec30e4c494ba7 0.001811 **
## x2_2600ab685c2ccb118a862f0b1b0fbfe9 0.004206 **
## x2_269233ab85f379500360ab847b8d11a4 0.0000165115206454 ***
## x2_269db099fcbd8d7208fdb4037d494f04 0.0000187907678823 ***
## x2_27c681dfdc5645ac249a286ff323e199 0.118693
## x2_28091686563aa5bf4f45adeacf5d32d5 0.057654 .
## x2_29eeae90a43111aded5d4ddfa484b23b 0.101999
## x2_2aa97dc7b655139fc9ffce352bd24bb7 0.244244
## x2_2ac9300a0de10e89f00a0e1051e60856 0.365744
## x2_2ad7485f19d0d21d4925dd4d1f61ee99 0.122120
## x2_2b361d80db361c7a17231a1ef2f4c6a4 0.001808 **
## x2_2cc907f118a60f20fc2cc7f76ceab68c 0.975763
## x2_2d0e68fc2b86d6d30e9c58fa3f11ef9a 0.882044
## x2_2d5ba9a7ce396fd5346d904637cc5b0a 0.030470 *
## x2_2daf09273f61b2b3381d0c70e1b57ec9 0.007624 **
## x2_2df51fa699005c6c64657e84098fd71f 0.600360
## x2_2dfdd7b8b57761e27d9b375c1142cfb2 0.325348
## x2_2eb500524b319bea908cf9560d4769cf 0.440011
## x2_2f0908f9b527b1f5cdfbf6e60d362027 0.000122 ***
## x2_2f4a170c729935052b0fda3e3cbe8625 0.298723
## x2_30043a051ec95cdfc753cde5c92deaa0 0.000116 ***
## x2_30108c80885d8f9449e3bdd6b6ecd5da 0.314874
## x2_30811f6f82e75fb157e8b93258861b0d 0.0000020742780262 ***
## x2_30dd738797f8299c7da368fc95e9eeab 0.000180 ***
## x2_30f21b7c216d85b772cc3146d3f9f4d4 0.154325
## x2_3116a5793171246adbf43fe55e4ef2d1 0.041207 *
## x2_32102a7c9d207b774b08d3195798ce26 0.018445 *
## x2_3355d31b8759d7561093c6f0dfa767db 0.267317
## x2_33616573b4c22e175077dcd1cade96b6 0.0000038277853250 ***
## x2_33f86129aacde1b8f08541d592d62661 0.000187 ***
## x2_34875e7da08b524a0079f442d2059f7c 0.000951 ***
## x2_35058dc89e09473f18e9b215d322e144 0.684140
## x2_3509c44a5b1ff31cee9a4878f81c6ecc 0.774902
## x2_350a633119d1a59162b15a33fa0f7861 0.002309 **
## x2_356b8ffa4b7beae198ced54c31e2162d 0.002507 **
## x2_359df4d63615570eba6759aca0a55226 0.000472 ***
## x2_3623e78af73768e45140372a2ebd4cf1 0.580784
## x2_3673d435b5dd04bf22417eb19cb58c80 0.432652
## x2_367667c7267dbf6425bc6b93a8f73405 0.005992 **
## x2_368863f45545d0ece1402cfac3ff8380 0.709487
## x2_369c07e037bdf9071badfa06c0f6ef4e 0.000634 ***
## x2_371ddf3fa48c25be8e3d6d506f1d5906 0.040683 *
## x2_386dc569766aca34389baa6ed194bcab 0.599767
## x2_38c1f83b8003d3e128291b3d7c3a330b 0.000113 ***
## x2_38e6c6964bb4152252a85b27d9957da3 0.003435 **
## x2_38f62052d64569daf6053dab488e3065 0.386217
## x2_397a9138fda0c210d7da5a4a839a3589 0.001158 **
## x2_39c560a0732e0fd890f781f012b23f49 0.821545
## x2_3aa42ca2e840818784f226b985bc9629 0.0000000115534978 ***
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## x24_9 0.053378 .
## x24_10 NA
## x24_11 0.176480
## x24_12 NA
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## x25_2 0.0000000000317100 ***
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## x25_4 < 0.0000000000000002 ***
## x25_5 < 0.0000000000000002 ***
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## x26_2 0.280110
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## x29_5 0.191895
## x29_6 0.385645
## x29_7 0.292061
## x29_8 NA
## x29_9 NA
## x29_10 NA
## x29_11 NA
## x29_12 NA
## x29_14 NA
## x29_16 NA
## x30_2 0.548507
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## x32_12 0.450229
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## x32_14 NA
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## x33_2 0.310882
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## x33_15 0.075370 .
## x33_16 0.020790 *
## x35_7 NA
## x35_8 NA
## x35_9 NA
## x35_16 NA
## x36_2 0.442077
## x36_3 0.450344
## x36_4 0.474381
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## x42_15 NA
## x42_16 NA
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## x44_16 NA
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## x47_14 NA
## x47_15 NA
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## x48_3 NA
## x48_7 0.671247
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## x48_9 0.928149
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## x48_13 NA
## x48_14 NA
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## x49_2 0.894306
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## x54_6 0.0000002478387916 ***
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## x60_13 NA
## x60_14 NA
## x60_15 NA
## x60_16 NA
## x61_2 0.458598
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## x64_2 0.870252
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## x64_7 NA
## x64_8 NA
## x64_9 NA
## x64_10 NA
## x64_11 NA
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## x64_16 NA
## x65_2 0.000267 ***
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## x69_2 0.579588
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## x70_2 0.235639
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## x71_11 NA
## x71_12 0.660381
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## x73_2 0.791585
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## x73_15 NA
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## x76_5 NA
## x76_6 NA
## x76_7 NA
## x76_8 NA
## x76_9 NA
## x76_10 NA
## x76_11 NA
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## x77_3 NA
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## x77_16 NA
## x79_2 0.001273 **
## x79_3 0.000200 ***
## x79_4 0.0000416686447184 ***
## x79_5 0.0000691775624744 ***
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## x80_10 0.549711
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## x81_11 0.549725
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## x81_13 0.449304
## x81_15 NA
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## x84_4 NA
## x84_5 NA
## x84_6 NA
## x84_7 NA
## x84_8 NA
## x84_9 NA
## x84_10 NA
## x84_11 NA
## x84_12 NA
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## x84_14 NA
## x84_15 NA
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## x85_7 NA
## x85_12 NA
## x85_13 NA
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## x85_16 NA
## x86_2 NA
## x86_3 0.352079
## x86_4 0.381106
## x86_5 0.427045
## x86_6 0.480688
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## x87_2 0.444337
## x87_3 0.616671
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## x88_9 NA
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## x89_2 0.682757
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## x106_8 0.304258
## x106_9 0.478857
## x106_10 0.088208 .
## x106_11 0.393744
## x106_12 NA
## x106_13 0.080262 .
## x106_14 0.148182
## x106_15 NA
## x106_16 0.999694
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.8735 on 12825 degrees of freedom
## Multiple R-squared: 0.7092, Adjusted R-squared: 0.6158
## F-statistic: 7.593 on 4119 and 12825 DF, p-value: < 0.00000000000000022Calculando os resíduos padronizados do modelo1
TrainSet_1$Val_pred <- predict(modelo1)
TrainSet_1$residuo <- resid(modelo1)
TrainSet_1$rp <- rstandard(modelo1)Erro quadratico medio na amostra de treino modelo1
# Erro quadratico medio na amostra de treino
mse1 <- mean((TrainSet_1$target - TrainSet_1$Val_pred)^2)
sqrt(mse1)## [1] 0.7599253Análise de resíduos modelo1
plot(predict(modelo1),TrainSet_1$residuo, xlab = "Preditor linear",ylab = "Residuos")
abline(h = 0, lty = 2)
qqnorm(residuals(modelo1), ylab="Residuos",xlab="Quantis teoricos",main="")
qqline(residuals(modelo1))
Excluindo os outliers modelo1
#Excluir os outliers
TrainSet_2 <-filter(TrainSet_1,TrainSet_1$rp>=-2&TrainSet_1$rp<=2)
#Pre-processamento dos dados
# Apaga a coluna
TrainSet_2$Val_pred = NULL
TrainSet_2$residuo = NULL
TrainSet_2$rp = NULLRodar o modelo
modelo2 <- lm(target ~ ., data = TrainSet_2)
summary(modelo2)##
## Call:
## lm(formula = target ~ ., data = TrainSet_2)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.59021 -0.37324 -0.03173 0.32560 2.35324
##
## Coefficients: (159 not defined because of singularities)
## Estimate Std. Error t value
## (Intercept) 7.6790029 2.3920544 3.210
## x13 -0.3014230 0.0197076 -15.295
## x14 0.1214667 0.0474139 2.562
## x18 0.4286496 0.0941348 4.554
## x20 -26.6584319 15.2924158 -1.743
## x21 -0.0867773 0.0246844 -3.515
## x22 1.9062504 0.7289786 2.615
## x34 0.1290902 0.0238762 5.407
## x45 -0.6717901 0.0197156 -34.074
## x50 -0.4625158 0.3587829 -1.289
## x56 0.1765028 0.0174345 10.124
## x72 0.0625947 0.0198903 3.147
## x74 -0.0645745 0.0196881 -3.280
## x75 -0.5446812 0.0162808 -33.455
## x82 -0.5321565 0.0197206 -26.985
## x83 0.1630914 0.0199288 8.184
## x90 0.0740146 0.3323629 0.223
## x92 -1.8977755 0.7747193 -2.450
## x94 0.7010521 0.0198604 35.299
## x101 25.7583111 15.2375800 1.690
## x105 0.3802848 0.1277941 2.976
## x2_009fdc2d37ffaba8e9854e5bf91e8193 0.9500438 0.1878327 5.058
## x2_0104f035fa3fd6867f97188b1f126c91 0.7774642 0.1856935 4.187
## x2_014498d37e0e50ffbd27edb7b87a02ce 0.6923080 0.1856470 3.729
## x2_01b5b97a96c69e9ee73b325b21a1093e 0.7912788 0.1912493 4.137
## x2_02949cb2e4502b1c382f48731eaa5d7d 1.4781174 0.1957124 7.552
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.5003705 0.1876450 2.667
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 -0.0727071 0.1901252 -0.382
## x2_03af349e980524ba204e4fdd09583887 -0.2444408 0.1927469 -1.268
## x2_03b7592ee764f088fa73a5964181d3eb 0.3893387 0.1984409 1.962
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## x39_14 0.5172414 0.5218527 0.991
## x39_15 0.8757996 0.5586243 1.568
## x39_16 NA NA NA
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## x42_15 NA NA NA
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## x46_16 NA NA NA
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## x47_14 NA NA NA
## x47_15 NA NA NA
## x47_16 NA NA NA
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## x48_14 NA NA NA
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## x60_12 NA NA NA
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## x64_7 NA NA NA
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## x69_15 NA NA NA
## x69_16 NA NA NA
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## x70_4 NA NA NA
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## x87_13 -0.5022672 0.7361123 -0.682
## x87_14 -0.4398726 0.7398582 -0.595
## x87_15 -0.4851291 0.7528336 -0.644
## x87_16 -0.3364247 0.7845040 -0.429
## x88_2 0.0014622 0.1751921 0.008
## x88_3 -0.2170517 0.3445823 -0.630
## x88_4 NA NA NA
## x88_5 0.8364515 0.7282097 1.149
## x88_6 NA NA NA
## x88_7 -0.9303910 0.7189109 -1.294
## x88_8 NA NA NA
## x88_9 NA NA NA
## x88_10 NA NA NA
## x88_11 NA NA NA
## x88_12 NA NA NA
## x88_13 NA NA NA
## x88_14 NA NA NA
## x88_16 NA NA NA
## x89_2 -0.0729414 0.2661600 -0.274
## x89_3 0.0400961 0.2471993 0.162
## x89_4 -0.0455547 0.2423491 -0.188
## x89_5 -0.0139071 0.2409045 -0.058
## x89_6 -0.0368680 0.2404292 -0.153
## x89_7 -0.0666188 0.2401498 -0.277
## x89_8 -0.1232071 0.2402658 -0.513
## x89_9 -0.0772849 0.2401999 -0.322
## x89_10 -0.0900038 0.2402773 -0.375
## x89_11 -0.0778141 0.2407944 -0.323
## x89_12 -0.0964781 0.2419466 -0.399
## x89_13 -0.1220538 0.2452356 -0.498
## x89_14 -0.1239858 0.2628360 -0.472
## x89_15 0.1696989 0.3035175 0.559
## x89_16 0.0328206 0.4010339 0.082
## x93_2 0.9687148 0.4777143 2.028
## x93_3 -0.1648126 0.4229242 -0.390
## x93_4 -0.2602613 0.4134444 -0.629
## x93_5 -0.1755656 0.4083667 -0.430
## x93_6 -0.2034559 0.4083145 -0.498
## x93_7 -0.3276809 0.4085357 -0.802
## x93_8 -0.3082382 0.4086333 -0.754
## x93_9 -0.2877207 0.4086104 -0.704
## x93_10 -0.2437813 0.4088406 -0.596
## x93_11 -0.1473647 0.4089026 -0.360
## x93_12 -0.2310589 0.4102571 -0.563
## x93_13 -0.1847868 0.4122418 -0.448
## x93_14 -0.1593739 0.4206328 -0.379
## x93_15 -0.2729425 0.4579985 -0.596
## x93_16 NA NA NA
## x95_2 0.2957264 0.5399246 0.548
## x95_3 0.0884202 0.5135558 0.172
## x95_4 -0.0434617 0.5083302 -0.085
## x95_5 -0.4087398 0.5062886 -0.807
## x95_6 -0.4577531 0.5059512 -0.905
## x95_7 -0.4311259 0.5058150 -0.852
## x95_8 -0.4605209 0.5057578 -0.911
## x95_9 -0.4357005 0.5057243 -0.862
## x95_10 -0.4141891 0.5055744 -0.819
## x95_11 -0.5004430 0.5055990 -0.990
## x95_12 -0.5855931 0.5056553 -1.158
## x95_13 -0.5575492 0.5060456 -1.102
## x95_14 -0.5609240 0.5068382 -1.107
## x95_15 -0.5827003 0.5107125 -1.141
## x95_16 -0.8158162 0.5473466 -1.490
## x96_2 -0.0193219 0.0456522 -0.423
## x96_3 0.0859509 0.0502071 1.712
## x96_4 0.0416639 0.0596453 0.699
## x96_5 0.0371726 0.0716456 0.519
## x96_6 -0.0139677 0.0860794 -0.162
## x96_7 -0.0405692 0.1037725 -0.391
## x96_8 -0.0636255 0.1280096 -0.497
## x96_9 0.1467530 0.1586201 0.925
## x96_10 0.2552819 0.2151397 1.187
## x96_11 0.5004878 0.2590502 1.932
## x96_12 0.7412648 0.3349269 2.213
## x96_13 2.6434801 0.6721892 3.933
## x96_14 1.8543327 0.7088011 2.616
## x96_15 NA NA NA
## x96_16 NA NA NA
## x97_16 -0.0485394 0.0302419 -1.605
## x98_2 0.1939632 0.3648779 0.532
## x98_3 0.0772973 0.3415758 0.226
## x98_4 0.1968429 0.3303222 0.596
## x98_5 0.0019862 0.3252340 0.006
## x98_6 0.0511037 0.3233445 0.158
## x98_7 0.0342949 0.3227656 0.106
## x98_8 0.0460693 0.3221395 0.143
## x98_9 0.0544310 0.3218059 0.169
## x98_10 0.0751113 0.3218285 0.233
## x98_11 0.0616284 0.3218025 0.192
## x98_12 0.2307688 0.3218470 0.717
## x98_13 0.2714166 0.3218697 0.843
## x98_14 0.3241877 0.3224571 1.005
## x98_15 0.2312047 0.3253987 0.711
## x98_16 0.3767596 0.3473961 1.085
## x99_2 -0.2222691 0.4689249 -0.474
## x99_3 -0.4235376 0.4231573 -1.001
## x99_4 -0.4945166 0.4175607 -1.184
## x99_5 -0.4016838 0.4157503 -0.966
## x99_6 -0.3907330 0.4150295 -0.941
## x99_7 -0.4090994 0.4148172 -0.986
## x99_8 -0.3997725 0.4148464 -0.964
## x99_9 -0.4221014 0.4148191 -1.018
## x99_10 -0.4061151 0.4149624 -0.979
## x99_11 -0.3394499 0.4149862 -0.818
## x99_12 -0.2831914 0.4154162 -0.682
## x99_13 -0.3285396 0.4164319 -0.789
## x99_14 -0.3783259 0.4204572 -0.900
## x99_15 -0.0645774 0.4406771 -0.147
## x99_16 -0.0979911 0.4745251 -0.207
## x102_2 0.5743416 0.3301694 1.740
## x102_3 0.2480289 0.2578243 0.962
## x102_4 0.3125076 0.2447502 1.277
## x102_5 -0.0462409 0.2415735 -0.191
## x102_6 -0.0781156 0.2408021 -0.324
## x102_7 -0.0695611 0.2406299 -0.289
## x102_8 -0.0296890 0.2403202 -0.124
## x102_9 -0.0484223 0.2402984 -0.202
## x102_10 -0.0560007 0.2404626 -0.233
## x102_11 -0.0871852 0.2406134 -0.362
## x102_12 0.0671569 0.2414290 0.278
## x102_13 0.0979244 0.2436885 0.402
## x102_14 0.1188595 0.2561084 0.464
## x102_15 0.1719719 0.2799604 0.614
## x102_16 0.3770788 0.5744762 0.656
## x103_3 -0.9079949 0.5708014 -1.591
## x103_4 -0.2185934 0.2724526 -0.802
## x103_5 -0.1839221 0.2458906 -0.748
## x103_6 -0.2995555 0.2409150 -1.243
## x103_7 -0.2675176 0.2396053 -1.116
## x103_8 -0.2532222 0.2392269 -1.059
## x103_9 -0.2469613 0.2390928 -1.033
## x103_10 -0.2417979 0.2391518 -1.011
## x103_11 -0.2655819 0.2392119 -1.110
## x103_12 -0.2656083 0.2395081 -1.109
## x103_13 -0.2290873 0.2406980 -0.952
## x103_14 -0.2056106 0.2434582 -0.845
## x103_15 -0.4850678 0.2560392 -1.895
## x103_16 NA NA NA
## x104_16 -0.1317804 0.0361539 -3.645
## x106_2 0.0354714 0.0145262 2.442
## x106_3 0.0589881 0.0169971 3.470
## x106_4 -0.0252965 0.0230682 -1.097
## x106_5 0.0014724 0.0322437 0.046
## x106_6 0.1240417 0.0485669 2.554
## x106_7 -0.2329314 0.0792395 -2.940
## x106_8 -0.0494562 0.0951809 -0.520
## x106_9 0.0127163 0.1450864 0.088
## x106_10 0.1952906 0.1938486 1.007
## x106_11 -0.1701721 0.2929154 -0.581
## x106_12 NA NA NA
## x106_13 0.9831906 0.4361221 2.254
## x106_14 NA NA NA
## x106_15 NA NA NA
## x106_16 0.0053072 0.5137674 0.010
## Pr(>|t|)
## (Intercept) 0.001330 **
## x13 < 0.0000000000000002 ***
## x14 0.010424 *
## x18 0.000005326090749677 ***
## x20 0.081316 .
## x21 0.000441 ***
## x22 0.008935 **
## x34 0.000000065438851019 ***
## x45 < 0.0000000000000002 ***
## x50 0.197380
## x56 < 0.0000000000000002 ***
## x72 0.001654 **
## x74 0.001042 **
## x75 < 0.0000000000000002 ***
## x82 < 0.0000000000000002 ***
## x83 0.000000000000000303 ***
## x90 0.823779
## x92 0.014314 *
## x94 < 0.0000000000000002 ***
## x101 0.090969 .
## x105 0.002928 **
## x2_009fdc2d37ffaba8e9854e5bf91e8193 0.000000430090383245 ***
## x2_0104f035fa3fd6867f97188b1f126c91 0.000028491388735540 ***
## x2_014498d37e0e50ffbd27edb7b87a02ce 0.000193 ***
## x2_01b5b97a96c69e9ee73b325b21a1093e 0.000035362153653888 ***
## x2_02949cb2e4502b1c382f48731eaa5d7d 0.000000000000045786 ***
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.007673 **
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 0.702159
## x2_03af349e980524ba204e4fdd09583887 0.204753
## x2_03b7592ee764f088fa73a5964181d3eb 0.049787 *
## x2_03be585b1ec66610133d1e369ea0bae0 0.005952 **
## x2_044c0dccd777a21ad32dfa271b25b05d 0.076360 .
## x2_04b5a9fbcede6d8da2c9443a74659508 0.942941
## x2_050e1afffbd1d7a2ae2d692e664e8cc6 0.697640
## x2_051d67c71a408ff3d1c5ef12bd4c4beb 0.614074
## x2_0527609acb9d3bb9f16229e4ea213155 0.000026998296810464 ***
## x2_053921d1e61fda98664a7cbc984b73bc 0.002331 **
## x2_055310e43ac25f3e7ce8d0197c029b05 0.000540 ***
## x2_05d62a51dc2cdb45015ac40846de7d2f 0.367619
## x2_063949e8aa1746c2f2072e3c3dfdf072 0.009236 **
## x2_06970c71617ff7923b250ac7ca9487a4 0.000334 ***
## x2_06fee204db920d6132334a5c3022b7f1 0.024293 *
## x2_087911c45b61db3e68a882004e37718c 0.000000002799531696 ***
## x2_08858f31ce8691322fa038d8660cf83e 0.275780
## x2_08e6c24b07efe1adef6bb2e463299f2d 0.002980 **
## x2_0a28dc4bccab65e38f0c53ba789c83ed 0.718723
## x2_0a69cf48a1af11b4d7a7ef215ffe8622 0.762135
## x2_0a72af1fa112ba359d30fee41d5f93fb 0.023908 *
## x2_0bc010c231ab369fff9c24dcb493a691 0.246810
## x2_0bda5d7eb1821a2ee9ad763276d4506e 0.486486
## x2_0c9e2bc33a3f374bb3640162acb5d17f 0.076179 .
## x2_0d07f17e244a25eb185c35a74c8933fd 0.062624 .
## x2_0dc4cab512b3206e5e1bc6cb09979f45 0.348455
## x2_0f485cf337eda5dd5944bec5a0b06ddf 0.000000405453078794 ***
## x2_0f7c19f51275e21407c8ce1288245eb2 0.159459
## x2_0feb9fe6a7fb9cdb87eb1d9fee3551aa 0.121449
## x2_104bee6dd94618d74bb624495714051f 0.199343
## x2_1075ca3a47325d5f4550b400dd22f7d3 0.806708
## x2_10dcfe9fc130743255177b8ff420e1f9 0.295187
## x2_10f6cfc6ab2a1637ec46f1fe47e40c74 0.110050
## x2_113c85f700a5e6e932baeaef711e1d7a 0.000207 ***
## x2_123d45ea021f01c2e2375c4b402d8991 0.669649
## x2_1267ff8f4bd26da9b5e5945f806709fd 0.000000013854578404 ***
## x2_129c5db8146f6531c8be44f5cdfe21e9 0.559720
## x2_12cf91889c40352fdf3ca6e9c4e4675b 0.000000563223635086 ***
## x2_131f0aac2bba6aa2b94dd9d77d9e25a0 0.590508
## x2_1486a0d04e430836dae79c9059576d1c 0.005814 **
## x2_14fe7f2dffd4dc845a66707864a7b660 0.005211 **
## x2_153df9695e96a68777e99c67982f5746 0.000067607533736130 ***
## x2_15e8e7d18fb7807216c66cdeb30692e9 0.000000124472834689 ***
## x2_171cde2526843878887a3223e5b70428 0.115241
## x2_172a0b2b81812459c08365129af5c789 0.549158
## x2_17b6c8d28a9009eb6595627926798a74 0.000273 ***
## x2_17c97746a154d137c62f0160b7f489ab 0.004226 **
## x2_17e1a8e1b27f98989ab96f75a2668a37 0.000869 ***
## x2_185c423535d71d45e9588031aac9cfa6 0.000277 ***
## x2_1920b9287379e68af3d06059beb79e69 0.346122
## x2_192f275f745cabe54420d4e03e682cf8 0.132636
## x2_197201b340da1e659a339b65729783be 0.412474
## x2_1a81ea262fea7bc80844206a444967c8 0.692409
## x2_1a834789d88f232251278c63050fc7cb 0.009598 **
## x2_1af39672631685e6ff064d3abbd88e4c 0.000116 ***
## x2_1b09d5cf03fa77d046fccb886172538a 0.076293 .
## x2_1c3cbc8aadd106d9719117bf1ba46cde 0.836034
## x2_1c4c1b63b9d3f03f2095a8ea32b9b12e 0.101336
## x2_1c5834c38ec7ea30ae8eb4f96c349c3f 0.112840
## x2_1d0d7838ce4c6a59c126e70417630238 0.000377 ***
## x2_1d38ae60450853859a40fec9ca958611 0.001635 **
## x2_1d4bbcb99529cb99db56adddbef3b1eb 0.871553
## x2_1eae3a63e85686b0287c0bc75b4f7505 0.678194
## x2_1ebc693367872184af173a1f06d4a1e6 0.797382
## x2_1effce387d172a9a92129b9f1fec4841 0.229321
## x2_1fe02ceb59ee78a2fcfd58c59af7e1bf 0.416090
## x2_207d151c484c92186932c013ddca15c9 0.000000027773766733 ***
## x2_20a2507337678a01558bb346e96230be 0.427285
## x2_20efb04ee762c2f69b47582e66c1c65b 0.001745 **
## x2_210a5a5f6e28f63665233225d386cfc6 0.190551
## x2_213083c1fd2d077ad9ee96f992c28e7b 0.494605
## x2_21f590ffa0c848a6346af02f54cdc4e3 0.536700
## x2_220aac87fa04588c5cc646f89c42aa21 0.783256
## x2_224e87ee9a8e53552f7f73235b0faf5c 0.488108
## x2_2338cc2081828b4ed26e7f37430ae0e0 0.750731
## x2_236a84ed3126415d7bfa0744c7ca3d72 0.802101
## x2_23c3ea3f5fce463108413f9335442fc3 0.091776 .
## x2_242b432d1edf79dc1c0e73eda036b590 0.000413 ***
## x2_24a76d3c6a139c738439aae8caa7be35 0.000000110367401980 ***
## x2_24f95a5010da08e96e7aa559a1cfd22d 0.963023
## x2_2536247d525726b531c14e8307612cb6 0.000010787648396509 ***
## x2_2585ed1efc11aa00042ec30e4c494ba7 0.000012524340919362 ***
## x2_2600ab685c2ccb118a862f0b1b0fbfe9 0.000067484744275568 ***
## x2_269233ab85f379500360ab847b8d11a4 0.000000000383138296 ***
## x2_269db099fcbd8d7208fdb4037d494f04 0.144312
## x2_27c681dfdc5645ac249a286ff323e199 0.080307 .
## x2_28091686563aa5bf4f45adeacf5d32d5 0.005179 **
## x2_29eeae90a43111aded5d4ddfa484b23b 0.030355 *
## x2_2aa97dc7b655139fc9ffce352bd24bb7 0.042416 *
## x2_2ac9300a0de10e89f00a0e1051e60856 0.246469
## x2_2ad7485f19d0d21d4925dd4d1f61ee99 0.288150
## x2_2b361d80db361c7a17231a1ef2f4c6a4 0.001158 **
## x2_2cc907f118a60f20fc2cc7f76ceab68c 0.778132
## x2_2d0e68fc2b86d6d30e9c58fa3f11ef9a 0.954888
## x2_2d5ba9a7ce396fd5346d904637cc5b0a 0.004698 **
## x2_2daf09273f61b2b3381d0c70e1b57ec9 0.000017553863537556 ***
## x2_2df51fa699005c6c64657e84098fd71f 0.624444
## x2_2dfdd7b8b57761e27d9b375c1142cfb2 0.243926
## x2_2eb500524b319bea908cf9560d4769cf 0.473605
## x2_2f0908f9b527b1f5cdfbf6e60d362027 0.000001245942255698 ***
## x2_2f4a170c729935052b0fda3e3cbe8625 0.449564
## x2_30043a051ec95cdfc753cde5c92deaa0 0.000003658016665356 ***
## x2_30108c80885d8f9449e3bdd6b6ecd5da 0.375881
## x2_30811f6f82e75fb157e8b93258861b0d 0.000000533261003159 ***
## x2_30dd738797f8299c7da368fc95e9eeab 0.000005395610487420 ***
## x2_30f21b7c216d85b772cc3146d3f9f4d4 0.031036 *
## x2_3116a5793171246adbf43fe55e4ef2d1 0.004536 **
## x2_32102a7c9d207b774b08d3195798ce26 0.017080 *
## x2_3355d31b8759d7561093c6f0dfa767db 0.322368
## x2_33616573b4c22e175077dcd1cade96b6 0.000000000821251939 ***
## x2_33f86129aacde1b8f08541d592d62661 0.000051790119808647 ***
## x2_34875e7da08b524a0079f442d2059f7c 0.000234 ***
## x2_35058dc89e09473f18e9b215d322e144 0.895054
## x2_3509c44a5b1ff31cee9a4878f81c6ecc 0.929435
## x2_350a633119d1a59162b15a33fa0f7861 0.000704 ***
## x2_356b8ffa4b7beae198ced54c31e2162d 0.002598 **
## x2_359df4d63615570eba6759aca0a55226 0.000067500887404712 ***
## x2_3623e78af73768e45140372a2ebd4cf1 0.860156
## x2_3673d435b5dd04bf22417eb19cb58c80 0.320567
## x2_367667c7267dbf6425bc6b93a8f73405 0.019987 *
## x2_368863f45545d0ece1402cfac3ff8380 0.887258
## x2_369c07e037bdf9071badfa06c0f6ef4e 0.000149 ***
## x2_371ddf3fa48c25be8e3d6d506f1d5906 0.015109 *
## x2_386dc569766aca34389baa6ed194bcab 0.882382
## x2_38c1f83b8003d3e128291b3d7c3a330b 0.000000114416761106 ***
## x2_38e6c6964bb4152252a85b27d9957da3 0.011524 *
## x2_38f62052d64569daf6053dab488e3065 0.133499
## x2_397a9138fda0c210d7da5a4a839a3589 0.000228 ***
## x2_39c560a0732e0fd890f781f012b23f49 0.815629
## x2_3aa42ca2e840818784f226b985bc9629 0.000002172967852285 ***
## x2_3aa4c976f41bb60488494c95ed6c6bba 0.007222 **
## x2_3ab095b5e61de32622e8cce0e611e752 0.000191 ***
## x2_3ad76e9c19ebc9dd18550b64a114b0cd 0.000074057350015997 ***
## x2_3af5b01bb233d99a246b53a4e245d94f 0.324490
## x2_3bcd58e81e1e7d093e41ed9193ddfdef 0.991760
## x2_3c9f174cf3f695799cc11998b6936617 0.300330
## x2_3ca53ec023fc382ee041f716fb88d2d0 0.000000004655173166 ***
## x2_3cb4c46bd235a4e4451b5270b96cfdc1 0.001516 **
## x2_3d1400872732a97bcab1828ada08f831 0.003612 **
## x2_3d15540c70bbe48c4098c891ac94d373 0.104257
## x2_3d2bf47c934519d5e2c1ef2895487aca 0.000584 ***
## x2_3e1c31c3ff0eb9fbb61ffc7cfa6242f8 0.791873
## x2_3e23bc0253b797991aada73bf356fd39 0.598163
## x2_3e5b5f4ae1b3ea9418ff57ae8e461604 0.000029647813378895 ***
## x2_3e627d02678fac75b90b71c9bd8c28e4 0.053805 .
## x2_3f74455132e7ca5cdbf7fa7d7a7333f7 0.652084
## x2_3fc7388fc326a445fb1e1cd4a54878f6 0.818006
## x2_3fc932a181da38b1d91d6a7facf47349 0.852009
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## x24_11 0.096325 .
## x24_12 NA
## x24_14 NA
## x24_16 NA
## x25_2 < 0.0000000000000002 ***
## x25_3 < 0.0000000000000002 ***
## x25_4 < 0.0000000000000002 ***
## x25_5 < 0.0000000000000002 ***
## x25_6 < 0.0000000000000002 ***
## x25_7 < 0.0000000000000002 ***
## x25_8 < 0.0000000000000002 ***
## x25_9 0.000000000000216856 ***
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## x25_15 0.000297 ***
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## x26_2 0.051401 .
## x26_3 0.004517 **
## x26_4 0.018892 *
## x26_5 0.013630 *
## x26_6 0.030739 *
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## x26_8 0.055914 .
## x26_9 0.020765 *
## x26_10 0.046817 *
## x26_11 0.185019
## x26_12 0.051814 .
## x26_13 0.034993 *
## x26_14 0.280952
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## x26_16 NA
## x29_2 0.668386
## x29_3 0.795067
## x29_4 0.307943
## x29_5 0.126822
## x29_6 0.269985
## x29_7 0.159890
## x29_8 NA
## x29_9 NA
## x29_10 NA
## x29_11 NA
## x29_12 NA
## x29_14 NA
## x29_16 NA
## x30_2 0.539340
## x30_3 0.531051
## x30_4 0.675583
## x30_5 0.714440
## x30_6 0.703607
## x30_7 0.808050
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## x30_10 0.870621
## x30_11 0.772569
## x30_12 0.680778
## x30_13 0.985320
## x30_14 0.597367
## x30_15 0.375143
## x30_16 NA
## x31_2 0.205515
## x31_3 0.907088
## x31_4 0.659357
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## x32_13 0.271275
## x32_14 NA
## x32_16 NA
## x33_2 0.148944
## x33_3 0.082780 .
## x33_4 0.051554 .
## x33_5 0.258212
## x33_6 0.282531
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## x33_12 0.000618 ***
## x33_13 0.357531
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## x33_15 0.001121 **
## x33_16 0.004717 **
## x35_7 NA
## x35_8 NA
## x35_9 NA
## x35_16 NA
## x36_2 0.884970
## x36_3 0.482653
## x36_4 0.448506
## x36_5 0.078578 .
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## x38_2 0.999360
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## x39_13 0.504735
## x39_14 0.321626
## x39_15 0.116959
## x39_16 NA
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## x40_4 0.482695
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## x40_15 NA
## x40_16 NA
## x41_2 0.086064 .
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## x42_11 0.361593
## x42_12 0.013028 *
## x42_13 0.065062 .
## x42_14 0.221131
## x42_15 NA
## x42_16 NA
## x43_2 0.742838
## x43_3 0.957373
## x43_4 0.924181
## x43_5 0.757666
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## x44_16 NA
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## x47_11 0.288026
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## x47_14 NA
## x47_15 NA
## x47_16 NA
## x48_3 NA
## x48_7 0.884554
## x48_8 0.787779
## x48_9 NA
## x48_10 0.674941
## x48_11 NA
## x48_13 NA
## x48_14 NA
## x48_16 NA
## x49_2 0.472361
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## x49_4 0.584550
## x49_5 0.802224
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## x54_13 0.607604
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## x55_12 0.985679
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## x55_14 NA
## x55_15 NA
## x55_16 NA
## x57_2 0.713316
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## x57_4 0.416336
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## x57_15 0.000281 ***
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## x58_2 NA
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## x58_5 0.299566
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## x60_7 0.237815
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## x60_11 0.477798
## x60_12 NA
## x60_13 NA
## x60_14 NA
## x60_15 NA
## x60_16 NA
## x61_2 0.520023
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## x61_4 0.384362
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## x63_11 NA
## x63_12 NA
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## x63_15 NA
## x63_16 NA
## x64_2 0.156033
## x64_3 0.995940
## x64_4 0.274897
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## x64_7 NA
## x64_8 NA
## x64_9 NA
## x64_10 NA
## x64_11 NA
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## x64_14 NA
## x64_16 NA
## x65_2 0.002492 **
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## x66_15 0.143302
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## x68_14 NA
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## x69_2 0.174505
## x69_3 0.099196 .
## x69_4 0.107875
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## x69_13 0.078123 .
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## x69_15 NA
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## x70_2 0.375145
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## x71_11 NA
## x71_12 0.427955
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## x73_2 0.427127
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## x73_16 NA
## x76_2 0.050829 .
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## x76_4 NA
## x76_5 NA
## x76_6 NA
## x76_7 NA
## x76_8 NA
## x76_9 NA
## x76_10 NA
## x76_11 NA
## x76_12 NA
## x76_13 NA
## x76_14 NA
## x76_15 NA
## x76_16 NA
## x77_3 NA
## x77_5 0.000734 ***
## x77_6 NA
## x77_16 NA
## x79_2 0.000001015346291294 ***
## x79_3 0.000000009944950799 ***
## x79_4 0.000000003825258677 ***
## x79_5 0.000000004023905295 ***
## x79_6 0.000000001219857172 ***
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## x79_14 0.000000108517554809 ***
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## x79_16 0.000488 ***
## x80_10 NA
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## x81_3 0.034801 *
## x81_4 0.885104
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## x81_12 0.948780
## x81_13 0.126735
## x81_15 NA
## x81_16 NA
## x84_2 NA
## x84_3 NA
## x84_4 NA
## x84_5 NA
## x84_6 NA
## x84_7 NA
## x84_8 NA
## x84_9 NA
## x84_10 NA
## x84_11 NA
## x84_12 NA
## x84_13 NA
## x84_14 NA
## x84_15 NA
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## x85_7 NA
## x85_12 NA
## x85_13 NA
## x85_14 NA
## x85_15 NA
## x85_16 NA
## x86_2 NA
## x86_3 0.518759
## x86_4 0.570843
## x86_5 0.628895
## x86_6 0.139001
## x86_7 NA
## x86_11 NA
## x86_14 NA
## x86_16 NA
## x87_2 0.727662
## x87_3 0.812297
## x87_4 0.671833
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## x88_3 0.528773
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## x88_7 0.195632
## x88_8 NA
## x88_9 NA
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## x88_11 NA
## x88_12 NA
## x88_13 NA
## x88_14 NA
## x88_16 NA
## x89_2 0.784050
## x89_3 0.871150
## x89_4 0.850902
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## x93_16 NA
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## x96_11 0.053382 .
## x96_12 0.026902 *
## x96_13 0.000084488735779552 ***
## x96_14 0.008904 **
## x96_15 NA
## x96_16 NA
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## x98_2 0.595024
## x98_3 0.820975
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## x98_5 0.995128
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## x99_15 0.883497
## x99_16 0.836401
## x102_2 0.081966 .
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## x103_12 0.267463
## x103_13 0.341237
## x103_14 0.398384
## x103_15 0.058182 .
## x103_16 NA
## x104_16 0.000269 ***
## x106_2 0.014625 *
## x106_3 0.000521 ***
## x106_4 0.272839
## x106_5 0.963579
## x106_6 0.010660 *
## x106_7 0.003293 **
## x106_8 0.603350
## x106_9 0.930159
## x106_10 0.313744
## x106_11 0.561278
## x106_12 NA
## x106_13 0.024189 *
## x106_14 NA
## x106_15 NA
## x106_16 0.991758
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.6249 on 12021 degrees of freedom
## Multiple R-squared: 0.7588, Adjusted R-squared: 0.6765
## F-statistic: 9.221 on 4102 and 12021 DF, p-value: < 0.00000000000000022TrainSet_2$Val_pred <- predict(modelo2)
TrainSet_2$residuo <- resid(modelo2)
TrainSet_2$rp <- rstandard(modelo2)df_analise2 <- TrainSet_2 %>%
select(target, Val_pred, residuo, rp)# Erro quadratico medio na amostra de treino
mse2 <- mean((TrainSet_2$target - TrainSet_2$Val_pred)^2)
sqrt(mse2)## [1] 0.5395849Análise dos resíduos do modelo
plot(predict(modelo2),TrainSet_2$residuo, xlab = "Preditor linear",ylab = "Residuos")
abline(h = 0, lty = 2)
qqnorm(residuals(modelo2), ylab="Residuos",xlab="Quantis teoricos",main="")
qqline(residuals(modelo2))
#Excluir os outliers
TrainSet_3 <-filter(TrainSet_2,TrainSet_2$rp>=-2&TrainSet_2$rp<=2)
#Pre-processamento dos dados
# Apaga a coluna
TrainSet_3$Val_pred = NULL
TrainSet_3$residuo = NULL
TrainSet_3$rp = NULLRodar o modelo
modelo3 <- lm(target ~ ., data = TrainSet_3)
summary(modelo3)##
## Call:
## lm(formula = target ~ ., data = TrainSet_3)
##
## Residuals:
## Min 1Q Median 3Q Max
## -1.19606 -0.30024 -0.02125 0.27453 1.61198
##
## Coefficients: (168 not defined because of singularities)
## Estimate Std. Error t value
## (Intercept) 6.4055299 1.8773053 3.412
## x13 -0.2806240 0.0161292 -17.398
## x14 0.0931409 0.0389513 2.391
## x18 0.3514005 0.0772530 4.549
## x20 -18.4912397 12.5376269 -1.475
## x21 -0.0869997 0.0202035 -4.306
## x22 0.9514555 0.6020313 1.580
## x34 0.1109304 0.0195294 5.680
## x45 -0.6014661 0.0161250 -37.300
## x50 -0.8765610 0.2948816 -2.973
## x56 0.1645619 0.0143038 11.505
## x72 0.0585432 0.0163356 3.584
## x74 -0.0617688 0.0161429 -3.826
## x75 -0.4851181 0.0133662 -36.295
## x82 -0.4827092 0.0161826 -29.829
## x83 0.1453798 0.0163493 8.892
## x90 0.4890653 0.2730858 1.791
## x92 -0.8960066 0.6398701 -1.400
## x94 0.6164751 0.0163069 37.805
## x101 17.7046548 12.4926936 1.417
## x105 0.3779191 0.1048063 3.606
## x2_009fdc2d37ffaba8e9854e5bf91e8193 0.9820258 0.1571549 6.249
## x2_0104f035fa3fd6867f97188b1f126c91 0.7911752 0.1556646 5.083
## x2_014498d37e0e50ffbd27edb7b87a02ce 0.7094318 0.1538486 4.611
## x2_01b5b97a96c69e9ee73b325b21a1093e 0.7499106 0.1564535 4.793
## x2_02949cb2e4502b1c382f48731eaa5d7d 1.4883277 0.1630165 9.130
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.6104537 0.1536458 3.973
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 -0.0169673 0.1537701 -0.110
## x2_03af349e980524ba204e4fdd09583887 -0.1609141 0.1560783 -1.031
## x2_03b7592ee764f088fa73a5964181d3eb 0.4412667 0.1629166 2.709
## x2_03be585b1ec66610133d1e369ea0bae0 0.5659650 0.1441080 3.927
## x2_044c0dccd777a21ad32dfa271b25b05d -0.1943823 0.1469400 -1.323
## x2_04b5a9fbcede6d8da2c9443a74659508 -0.0085422 0.1611967 -0.053
## x2_050e1afffbd1d7a2ae2d692e664e8cc6 0.0207537 0.1394200 0.149
## x2_051d67c71a408ff3d1c5ef12bd4c4beb 0.0314134 0.1477679 0.213
## x2_0527609acb9d3bb9f16229e4ea213155 0.6961892 0.1540232 4.520
## x2_053921d1e61fda98664a7cbc984b73bc 0.6034537 0.1499280 4.025
## x2_055310e43ac25f3e7ce8d0197c029b05 0.7690689 0.1781181 4.318
## x2_05d62a51dc2cdb45015ac40846de7d2f -0.0977918 0.1429060 -0.684
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## x2_06970c71617ff7923b250ac7ca9487a4 0.6975423 0.1435104 4.861
## x2_06fee204db920d6132334a5c3022b7f1 0.4142795 0.1469240 2.820
## x2_087911c45b61db3e68a882004e37718c 1.2812918 0.1554943 8.240
## x2_08858f31ce8691322fa038d8660cf83e 0.3368143 0.1493522 2.255
## x2_08e6c24b07efe1adef6bb2e463299f2d 0.4789764 0.1905099 2.514
## x2_0a28dc4bccab65e38f0c53ba789c83ed 0.0441368 0.1432725 0.308
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## x1_15 NA NA NA
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## x11_12 NA NA NA
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## x39_12 0.3595816 0.4143553 0.868
## x39_13 0.3091860 0.4151857 0.745
## x39_14 0.4608490 0.4192845 1.099
## x39_15 0.9666732 0.4481598 2.157
## x39_16 NA NA NA
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## x40_13 0.1545671 0.1788871 0.864
## x40_14 0.3719379 0.2048785 1.815
## x40_15 NA NA NA
## x40_16 NA NA NA
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## x42_15 NA NA NA
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## x44_16 NA NA NA
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## x46_16 NA NA NA
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## x47_13 -0.0870926 0.3346511 -0.260
## x47_14 NA NA NA
## x47_15 NA NA NA
## x47_16 NA NA NA
## x48_3 NA NA NA
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## x48_8 0.0410977 0.4163209 0.099
## x48_9 NA NA NA
## x48_10 0.1521470 0.5204398 0.292
## x48_11 NA NA NA
## x48_13 NA NA NA
## x48_14 NA NA NA
## x48_16 NA NA NA
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## x49_3 0.0152312 0.2983567 0.051
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## x52_14 0.8376005 0.4050572 2.068
## x52_16 NA NA NA
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## x54_3 0.0339978 0.0146366 2.323
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## x54_5 -0.0103834 0.0237626 -0.437
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## x54_10 0.9261946 0.1178883 7.857
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## x54_13 0.2853347 0.4119575 0.693
## x54_14 0.5763046 0.4113947 1.401
## x54_15 NA NA NA
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## x55_14 NA NA NA
## x55_15 NA NA NA
## x55_16 NA NA NA
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## x57_15 1.7045824 0.4109168 4.148
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## x58_2 NA NA NA
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## x58_4 0.3978388 0.2013728 1.976
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## x58_16 NA NA NA
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## x60_12 NA NA NA
## x60_13 NA NA NA
## x60_14 NA NA NA
## x60_15 NA NA NA
## x60_16 NA NA NA
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## x63_9 0.5773385 0.5594480 1.032
## x63_10 NA NA NA
## x63_11 NA NA NA
## x63_12 NA NA NA
## x63_13 NA NA NA
## x63_14 NA NA NA
## x63_15 NA NA NA
## x63_16 NA NA NA
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## x64_6 0.0399417 0.6495915 0.061
## x64_7 NA NA NA
## x64_8 NA NA NA
## x64_9 NA NA NA
## x64_10 NA NA NA
## x64_11 NA NA NA
## x64_12 NA NA NA
## x64_14 NA NA NA
## x64_16 NA NA NA
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## x65_4 0.0021098 0.0187838 0.112
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## x65_15 NA NA NA
## x65_16 -0.5144032 0.4096864 -1.256
## x66_7 NA NA NA
## x66_12 NA NA NA
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## x66_14 0.4214572 0.3364812 1.253
## x66_15 0.6837106 0.4763829 1.435
## x66_16 NA NA NA
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## x68_16 NA NA NA
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## x69_5 0.3729654 0.2192644 1.701
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## x69_15 NA NA NA
## x69_16 NA NA NA
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## x70_3 0.8200509 0.3341348 2.454
## x70_4 NA NA NA
## x70_16 NA NA NA
## x71_11 NA NA NA
## x71_12 0.6478187 0.4486234 1.444
## x71_13 0.7271285 0.4057763 1.792
## x71_14 NA NA NA
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## x73_15 NA NA NA
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## x76_6 NA NA NA
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## x81_15 NA NA NA
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## x84_2 NA NA NA
## x84_3 NA NA NA
## x84_4 NA NA NA
## x84_5 NA NA NA
## x84_6 NA NA NA
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## x85_14 NA NA NA
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## x85_16 NA NA NA
## x86_2 NA NA NA
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## x86_4 0.0878737 0.4094039 0.215
## x86_5 0.0731502 0.4101633 0.178
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## x86_7 NA NA NA
## x86_11 NA NA NA
## x86_14 NA NA NA
## x86_16 NA NA NA
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## x87_3 0.2133614 0.2743670 0.778
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## x87_14 -0.0538243 0.2758806 -0.195
## x87_15 -0.0044202 0.2975297 -0.015
## x87_16 NA NA NA
## x88_2 0.0327902 0.1399136 0.234
## x88_3 -0.2180724 0.2753754 -0.792
## x88_4 NA NA NA
## x88_5 NA NA NA
## x88_6 NA NA NA
## x88_7 -0.8152931 0.5726244 -1.424
## x88_8 NA NA NA
## x88_9 NA NA NA
## x88_10 NA NA NA
## x88_11 NA NA NA
## x88_12 NA NA NA
## x88_13 NA NA NA
## x88_14 NA NA NA
## x88_16 NA NA NA
## x89_2 -0.1094118 0.2246842 -0.487
## x89_3 0.0986152 0.2093013 0.471
## x89_4 0.0450779 0.2051172 0.220
## x89_5 0.0355615 0.2039760 0.174
## x89_6 0.0347263 0.2036075 0.171
## x89_7 0.0143738 0.2033604 0.071
## x89_8 -0.0359276 0.2034623 -0.177
## x89_9 0.0057859 0.2033842 0.028
## x89_10 -0.0043980 0.2034786 -0.022
## x89_11 0.0058820 0.2039033 0.029
## x89_12 -0.0146299 0.2048883 -0.071
## x89_13 -0.0081432 0.2073959 -0.039
## x89_14 -0.0607731 0.2211474 -0.275
## x89_15 0.0220816 0.2588975 0.085
## x89_16 -0.3621936 0.3495183 -1.036
## x93_2 0.2989251 0.3978599 0.751
## x93_3 -0.2522101 0.3393044 -0.743
## x93_4 -0.3991739 0.3297967 -1.210
## x93_5 -0.2388346 0.3254371 -0.734
## x93_6 -0.2680403 0.3254071 -0.824
## x93_7 -0.3704266 0.3256097 -1.138
## x93_8 -0.3451345 0.3256530 -1.060
## x93_9 -0.3281207 0.3256529 -1.008
## x93_10 -0.2920085 0.3258434 -0.896
## x93_11 -0.2069037 0.3258753 -0.635
## x93_12 -0.2837013 0.3270521 -0.867
## x93_13 -0.1827705 0.3285496 -0.556
## x93_14 -0.2069051 0.3354768 -0.617
## x93_15 -0.2336224 0.3650069 -0.640
## x93_16 NA NA NA
## x95_2 0.4307991 0.4306767 1.000
## x95_3 0.2144096 0.4098762 0.523
## x95_4 0.0609180 0.4054454 0.150
## x95_5 -0.2707690 0.4036172 -0.671
## x95_6 -0.2839412 0.4033663 -0.704
## x95_7 -0.2878329 0.4033010 -0.714
## x95_8 -0.2879265 0.4032150 -0.714
## x95_9 -0.2719891 0.4032174 -0.675
## x95_10 -0.2612178 0.4030745 -0.648
## x95_11 -0.3285912 0.4031105 -0.815
## x95_12 -0.4126133 0.4031187 -1.024
## x95_13 -0.3911834 0.4034784 -0.970
## x95_14 -0.3810800 0.4041237 -0.943
## x95_15 -0.4441032 0.4076426 -1.089
## x95_16 -0.5030175 0.4435968 -1.134
## x96_2 -0.0225253 0.0372052 -0.605
## x96_3 0.0654291 0.0409679 1.597
## x96_4 0.0303965 0.0487184 0.624
## x96_5 -0.0161287 0.0586816 -0.275
## x96_6 -0.0185311 0.0706230 -0.262
## x96_7 -0.0520746 0.0853017 -0.610
## x96_8 -0.0572984 0.1053041 -0.544
## x96_9 0.1437714 0.1312378 1.096
## x96_10 0.0282200 0.1770305 0.159
## x96_11 0.2757354 0.2171706 1.270
## x96_12 0.5460875 0.2825059 1.933
## x96_13 NA NA NA
## x96_14 1.8376382 0.5736323 3.204
## x96_15 NA NA NA
## x96_16 NA NA NA
## x97_16 -0.0519576 0.0245984 -2.112
## x98_2 0.0447811 0.3020462 0.148
## x98_3 -0.0522784 0.2736039 -0.191
## x98_4 0.0960129 0.2641151 0.364
## x98_5 -0.0656302 0.2597815 -0.253
## x98_6 -0.0562675 0.2582334 -0.218
## x98_7 -0.0646244 0.2577331 -0.251
## x98_8 -0.0694348 0.2571952 -0.270
## x98_9 -0.0316641 0.2569351 -0.123
## x98_10 -0.0145773 0.2569431 -0.057
## x98_11 -0.0289297 0.2569198 -0.113
## x98_12 0.1259466 0.2569596 0.490
## x98_13 0.1487824 0.2569940 0.579
## x98_14 0.1850052 0.2574684 0.719
## x98_15 0.0888320 0.2599934 0.342
## x98_16 0.1207161 0.2794090 0.432
## x99_2 -0.3837432 0.3783564 -1.014
## x99_3 -0.4430023 0.3376796 -1.312
## x99_4 -0.5726461 0.3332276 -1.718
## x99_5 -0.4524986 0.3316904 -1.364
## x99_6 -0.4583558 0.3310453 -1.385
## x99_7 -0.4667253 0.3308781 -1.411
## x99_8 -0.4705406 0.3308876 -1.422
## x99_9 -0.4822712 0.3308483 -1.458
## x99_10 -0.4736495 0.3309755 -1.431
## x99_11 -0.4030688 0.3310119 -1.218
## x99_12 -0.3460651 0.3314401 -1.044
## x99_13 -0.3912388 0.3322249 -1.178
## x99_14 -0.3872596 0.3357479 -1.153
## x99_15 0.0491009 0.3531157 0.139
## x99_16 -0.0705149 0.3790333 -0.186
## x102_2 0.4509998 0.2885277 1.563
## x102_3 -0.0522215 0.2176646 -0.240
## x102_4 0.0021490 0.2075124 0.010
## x102_5 -0.3429353 0.2049024 -1.674
## x102_6 -0.3348388 0.2042728 -1.639
## x102_7 -0.3461552 0.2041440 -1.696
## x102_8 -0.2965225 0.2039000 -1.454
## x102_9 -0.3152205 0.2038515 -1.546
## x102_10 -0.3339710 0.2039954 -1.637
## x102_11 -0.3500514 0.2041070 -1.715
## x102_12 -0.2009600 0.2047407 -0.982
## x102_13 -0.1788165 0.2065179 -0.866
## x102_14 -0.1658436 0.2161006 -0.767
## x102_15 -0.0697217 0.2341107 -0.298
## x102_16 0.1218898 0.4637452 0.263
## x103_3 -0.8805247 0.4606532 -1.911
## x103_4 -0.1743636 0.2307017 -0.756
## x103_5 -0.1679089 0.2082468 -0.806
## x103_6 -0.2154870 0.2044031 -1.054
## x103_7 -0.2178547 0.2033073 -1.072
## x103_8 -0.1935613 0.2030056 -0.953
## x103_9 -0.1869290 0.2029148 -0.921
## x103_10 -0.1805234 0.2029368 -0.890
## x103_11 -0.2087667 0.2029886 -1.028
## x103_12 -0.2189726 0.2032138 -1.078
## x103_13 -0.1987328 0.2041585 -0.973
## x103_14 -0.1637984 0.2064306 -0.793
## x103_15 -0.3589448 0.2163562 -1.659
## x103_16 NA NA NA
## x104_16 -0.0996782 0.0296611 -3.361
## x106_2 0.0328855 0.0119208 2.759
## x106_3 0.0529967 0.0139520 3.799
## x106_4 -0.0216445 0.0188560 -1.148
## x106_5 -0.0184160 0.0263864 -0.698
## x106_6 0.0919974 0.0401943 2.289
## x106_7 -0.1606936 0.0637435 -2.521
## x106_8 -0.0020121 0.0782681 -0.026
## x106_9 0.0901762 0.1159319 0.778
## x106_10 -0.0615831 0.1675640 -0.368
## x106_11 0.0832128 0.2561986 0.325
## x106_12 NA NA NA
## x106_13 1.6659481 0.3994685 4.170
## x106_14 NA NA NA
## x106_15 NA NA NA
## x106_16 -0.0318815 0.4096267 -0.078
## Pr(>|t|)
## (Intercept) 0.000647 ***
## x13 < 0.0000000000000002 ***
## x14 0.016809 *
## x18 0.00000545455606155 ***
## x20 0.140278
## x21 0.00001675109655347 ***
## x22 0.114041
## x34 0.00000001379044904 ***
## x45 < 0.0000000000000002 ***
## x50 0.002959 **
## x56 < 0.0000000000000002 ***
## x72 0.000340 ***
## x74 0.000131 ***
## x75 < 0.0000000000000002 ***
## x82 < 0.0000000000000002 ***
## x83 < 0.0000000000000002 ***
## x90 0.073339 .
## x92 0.161453
## x94 < 0.0000000000000002 ***
## x101 0.156452
## x105 0.000312 ***
## x2_009fdc2d37ffaba8e9854e5bf91e8193 0.00000000042867358 ***
## x2_0104f035fa3fd6867f97188b1f126c91 0.00000037837325795 ***
## x2_014498d37e0e50ffbd27edb7b87a02ce 0.00000404710834033 ***
## x2_01b5b97a96c69e9ee73b325b21a1093e 0.00000166261184533 ***
## x2_02949cb2e4502b1c382f48731eaa5d7d < 0.0000000000000002 ***
## x2_02d0d60a0ebfea498fd89b0de001c8d7 0.00007137996974427 ***
## x2_02dc5d0d09d6626dd19b4bc29bafe0b1 0.912140
## x2_03af349e980524ba204e4fdd09583887 0.302571
## x2_03b7592ee764f088fa73a5964181d3eb 0.006768 **
## x2_03be585b1ec66610133d1e369ea0bae0 0.00008639475931205 ***
## x2_044c0dccd777a21ad32dfa271b25b05d 0.185906
## x2_04b5a9fbcede6d8da2c9443a74659508 0.957739
## x2_050e1afffbd1d7a2ae2d692e664e8cc6 0.881669
## x2_051d67c71a408ff3d1c5ef12bd4c4beb 0.831653
## x2_0527609acb9d3bb9f16229e4ea213155 0.00000624638803985 ***
## x2_053921d1e61fda98664a7cbc984b73bc 0.00005736000256488 ***
## x2_055310e43ac25f3e7ce8d0197c029b05 0.00001589828917184 ***
## x2_05d62a51dc2cdb45015ac40846de7d2f 0.493795
## x2_063949e8aa1746c2f2072e3c3dfdf072 0.000134 ***
## x2_06970c71617ff7923b250ac7ca9487a4 0.00000118633018914 ***
## x2_06fee204db920d6132334a5c3022b7f1 0.004816 **
## x2_087911c45b61db3e68a882004e37718c < 0.0000000000000002 ***
## x2_08858f31ce8691322fa038d8660cf83e 0.024142 *
## x2_08e6c24b07efe1adef6bb2e463299f2d 0.011945 *
## x2_0a28dc4bccab65e38f0c53ba789c83ed 0.758041
## x2_0a69cf48a1af11b4d7a7ef215ffe8622 0.883705
## x2_0a72af1fa112ba359d30fee41d5f93fb 0.047859 *
## x2_0bc010c231ab369fff9c24dcb493a691 0.880306
## x2_0bda5d7eb1821a2ee9ad763276d4506e 0.608333
## x2_0c9e2bc33a3f374bb3640162acb5d17f 0.199158
## x2_0d07f17e244a25eb185c35a74c8933fd 0.494497
## x2_0dc4cab512b3206e5e1bc6cb09979f45 0.238302
## x2_0f485cf337eda5dd5944bec5a0b06ddf 0.00000000003675086 ***
## x2_0f7c19f51275e21407c8ce1288245eb2 0.009788 **
## x2_0feb9fe6a7fb9cdb87eb1d9fee3551aa 0.388521
## x2_104bee6dd94618d74bb624495714051f 0.265547
## x2_1075ca3a47325d5f4550b400dd22f7d3 0.728807
## x2_10dcfe9fc130743255177b8ff420e1f9 0.557760
## x2_10f6cfc6ab2a1637ec46f1fe47e40c74 0.044549 *
## x2_113c85f700a5e6e932baeaef711e1d7a 0.00002083205274923 ***
## x2_123d45ea021f01c2e2375c4b402d8991 0.312105
## x2_1267ff8f4bd26da9b5e5945f806709fd 0.00000000001379693 ***
## x2_129c5db8146f6531c8be44f5cdfe21e9 0.185340
## x2_12cf91889c40352fdf3ca6e9c4e4675b 0.00000043585570251 ***
## x2_131f0aac2bba6aa2b94dd9d77d9e25a0 0.592938
## x2_1486a0d04e430836dae79c9059576d1c 0.000187 ***
## x2_14fe7f2dffd4dc845a66707864a7b660 0.001734 **
## x2_153df9695e96a68777e99c67982f5746 0.00000149346946044 ***
## x2_15e8e7d18fb7807216c66cdeb30692e9 0.00000000157413501 ***
## x2_171cde2526843878887a3223e5b70428 0.154619
## x2_172a0b2b81812459c08365129af5c789 0.903729
## x2_17b6c8d28a9009eb6595627926798a74 0.00000027436808876 ***
## x2_17c97746a154d137c62f0160b7f489ab 0.000805 ***
## x2_17e1a8e1b27f98989ab96f75a2668a37 0.00004959529774416 ***
## x2_185c423535d71d45e9588031aac9cfa6 0.00000018433507699 ***
## x2_1920b9287379e68af3d06059beb79e69 0.341567
## x2_192f275f745cabe54420d4e03e682cf8 0.329999
## x2_197201b340da1e659a339b65729783be 0.872248
## x2_1a81ea262fea7bc80844206a444967c8 0.338314
## x2_1a834789d88f232251278c63050fc7cb 0.00004442206516081 ***
## x2_1af39672631685e6ff064d3abbd88e4c 0.000520 ***
## x2_1b09d5cf03fa77d046fccb886172538a 0.324973
## x2_1c3cbc8aadd106d9719117bf1ba46cde 0.707071
## x2_1c4c1b63b9d3f03f2095a8ea32b9b12e 0.531544
## x2_1c5834c38ec7ea30ae8eb4f96c349c3f 0.245620
## x2_1d0d7838ce4c6a59c126e70417630238 0.00000115030266798 ***
## x2_1d38ae60450853859a40fec9ca958611 0.00000144101659682 ***
## x2_1d4bbcb99529cb99db56adddbef3b1eb 0.644547
## x2_1eae3a63e85686b0287c0bc75b4f7505 0.169048
## x2_1ebc693367872184af173a1f06d4a1e6 0.527953
## x2_1effce387d172a9a92129b9f1fec4841 0.574068
## x2_1fe02ceb59ee78a2fcfd58c59af7e1bf 0.416932
## x2_207d151c484c92186932c013ddca15c9 0.00000000931742954 ***
## x2_20a2507337678a01558bb346e96230be 0.504339
## x2_20efb04ee762c2f69b47582e66c1c65b 0.000424 ***
## x2_210a5a5f6e28f63665233225d386cfc6 0.505552
## x2_213083c1fd2d077ad9ee96f992c28e7b 0.239769
## x2_21f590ffa0c848a6346af02f54cdc4e3 0.990064
## x2_220aac87fa04588c5cc646f89c42aa21 0.753780
## x2_224e87ee9a8e53552f7f73235b0faf5c 0.675460
## x2_2338cc2081828b4ed26e7f37430ae0e0 0.222907
## x2_236a84ed3126415d7bfa0744c7ca3d72 0.589357
## x2_23c3ea3f5fce463108413f9335442fc3 0.026673 *
## x2_242b432d1edf79dc1c0e73eda036b590 0.00005674439544725 ***
## x2_24a76d3c6a139c738439aae8caa7be35 0.00000000003412178 ***
## x2_24f95a5010da08e96e7aa559a1cfd22d 0.592862
## x2_2536247d525726b531c14e8307612cb6 0.00000003790850074 ***
## x2_2585ed1efc11aa00042ec30e4c494ba7 0.00000075092481148 ***
## x2_2600ab685c2ccb118a862f0b1b0fbfe9 0.00000000913627649 ***
## x2_269233ab85f379500360ab847b8d11a4 < 0.0000000000000002 ***
## x2_269db099fcbd8d7208fdb4037d494f04 0.238985
## x2_27c681dfdc5645ac249a286ff323e199 0.079338 .
## x2_28091686563aa5bf4f45adeacf5d32d5 0.001823 **
## x2_29eeae90a43111aded5d4ddfa484b23b 0.130583
## x2_2aa97dc7b655139fc9ffce352bd24bb7 0.038945 *
## x2_2ac9300a0de10e89f00a0e1051e60856 0.351828
## x2_2ad7485f19d0d21d4925dd4d1f61ee99 0.633175
## x2_2b361d80db361c7a17231a1ef2f4c6a4 0.00003167900510930 ***
## x2_2cc907f118a60f20fc2cc7f76ceab68c 0.975538
## x2_2d0e68fc2b86d6d30e9c58fa3f11ef9a 0.639320
## x2_2d5ba9a7ce396fd5346d904637cc5b0a 0.00000181583110507 ***
## x2_2daf09273f61b2b3381d0c70e1b57ec9 0.00000006986725180 ***
## x2_2df51fa699005c6c64657e84098fd71f 0.509935
## x2_2dfdd7b8b57761e27d9b375c1142cfb2 0.524261
## x2_2eb500524b319bea908cf9560d4769cf 0.406916
## x2_2f0908f9b527b1f5cdfbf6e60d362027 0.00000000244172047 ***
## x2_2f4a170c729935052b0fda3e3cbe8625 0.946619
## x2_30043a051ec95cdfc753cde5c92deaa0 0.00000000000830543 ***
## x2_30108c80885d8f9449e3bdd6b6ecd5da 0.155936
## x2_30811f6f82e75fb157e8b93258861b0d 0.00000002529213600 ***
## x2_30dd738797f8299c7da368fc95e9eeab 0.00000065921421743 ***
## x2_30f21b7c216d85b772cc3146d3f9f4d4 0.000769 ***
## x2_3116a5793171246adbf43fe55e4ef2d1 0.00003495339705399 ***
## x2_32102a7c9d207b774b08d3195798ce26 0.006257 **
## x2_3355d31b8759d7561093c6f0dfa767db 0.520199
## x2_33616573b4c22e175077dcd1cade96b6 0.00000000000068884 ***
## x2_33f86129aacde1b8f08541d592d62661 0.00000048164647200 ***
## x2_34875e7da08b524a0079f442d2059f7c 0.00003324626179661 ***
## x2_35058dc89e09473f18e9b215d322e144 0.962946
## x2_3509c44a5b1ff31cee9a4878f81c6ecc 0.370819
## x2_350a633119d1a59162b15a33fa0f7861 0.00009006538989148 ***
## x2_356b8ffa4b7beae198ced54c31e2162d 0.000832 ***
## x2_359df4d63615570eba6759aca0a55226 0.00000048240669754 ***
## x2_3623e78af73768e45140372a2ebd4cf1 0.739426
## x2_3673d435b5dd04bf22417eb19cb58c80 0.069942 .
## x2_367667c7267dbf6425bc6b93a8f73405 0.000424 ***
## x2_368863f45545d0ece1402cfac3ff8380 0.474119
## x2_369c07e037bdf9071badfa06c0f6ef4e 0.00001008325626762 ***
## x2_371ddf3fa48c25be8e3d6d506f1d5906 0.001018 **
## x2_386dc569766aca34389baa6ed194bcab 0.933200
## x2_38c1f83b8003d3e128291b3d7c3a330b 0.00000004877237702 ***
## x2_38e6c6964bb4152252a85b27d9957da3 0.001529 **
## x2_38f62052d64569daf6053dab488e3065 0.014923 *
## x2_397a9138fda0c210d7da5a4a839a3589 0.00000119581891738 ***
## x2_39c560a0732e0fd890f781f012b23f49 0.565816
## x2_3aa42ca2e840818784f226b985bc9629 0.00000170736503828 ***
## x2_3aa4c976f41bb60488494c95ed6c6bba 0.013502 *
## x2_3ab095b5e61de32622e8cce0e611e752 0.00000003722331483 ***
## x2_3ad76e9c19ebc9dd18550b64a114b0cd 0.00000002387401051 ***
## x2_3af5b01bb233d99a246b53a4e245d94f 0.761839
## x2_3bcd58e81e1e7d093e41ed9193ddfdef 0.318073
## x2_3c9f174cf3f695799cc11998b6936617 0.037623 *
## x2_3ca53ec023fc382ee041f716fb88d2d0 0.00000000000269674 ***
## x2_3cb4c46bd235a4e4451b5270b96cfdc1 0.003281 **
## x2_3d1400872732a97bcab1828ada08f831 0.00000763071196501 ***
## x2_3d15540c70bbe48c4098c891ac94d373 0.144371
## x2_3d2bf47c934519d5e2c1ef2895487aca 0.00003097950629079 ***
## x2_3e1c31c3ff0eb9fbb61ffc7cfa6242f8 0.996978
## x2_3e23bc0253b797991aada73bf356fd39 0.880173
## x2_3e5b5f4ae1b3ea9418ff57ae8e461604 0.00000010858634273 ***
## x2_3e627d02678fac75b90b71c9bd8c28e4 0.008450 **
## x2_3f74455132e7ca5cdbf7fa7d7a7333f7 0.789799
## x2_3fc7388fc326a445fb1e1cd4a54878f6 0.345238
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## x17_10 0.370662
## x17_11 0.400818
## x17_12 0.032929 *
## x17_13 0.844988
## x17_14 NA
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## x19_2 0.023102 *
## x19_3 0.002083 **
## x19_4 0.001580 **
## x19_5 0.003498 **
## x19_6 0.002419 **
## x19_7 0.002920 **
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## x23_12 0.482299
## x23_13 0.413763
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## x23_15 0.491460
## x23_16 NA
## x24_2 0.00000000000012643 ***
## x24_3 0.000555 ***
## x24_4 0.285229
## x24_5 0.310280
## x24_6 0.261996
## x24_7 0.163536
## x24_8 0.028115 *
## x24_9 NA
## x24_10 NA
## x24_11 0.039761 *
## x24_12 NA
## x24_14 NA
## x24_16 NA
## x25_2 < 0.0000000000000002 ***
## x25_3 < 0.0000000000000002 ***
## x25_4 < 0.0000000000000002 ***
## x25_5 < 0.0000000000000002 ***
## x25_6 < 0.0000000000000002 ***
## x25_7 < 0.0000000000000002 ***
## x25_8 < 0.0000000000000002 ***
## x25_9 < 0.0000000000000002 ***
## x25_10 0.00000000117653047 ***
## x25_11 0.00000040578956885 ***
## x25_12 0.257691
## x25_13 0.055885 .
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## x25_15 0.00002090549586664 ***
## x25_16 0.111602
## x26_2 0.069612 .
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## x26_4 0.044519 *
## x26_5 0.016624 *
## x26_6 0.038963 *
## x26_7 0.024833 *
## x26_8 0.057331 .
## x26_9 0.049254 *
## x26_10 0.048382 *
## x26_11 0.243452
## x26_12 0.049491 *
## x26_13 0.067586 .
## x26_14 0.381621
## x26_15 0.964090
## x26_16 NA
## x29_2 0.763963
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## x29_4 0.246726
## x29_5 0.488536
## x29_6 0.599346
## x29_7 0.055576 .
## x29_8 NA
## x29_9 NA
## x29_10 NA
## x29_11 NA
## x29_12 NA
## x29_14 NA
## x29_16 NA
## x30_2 0.542113
## x30_3 0.924262
## x30_4 0.980137
## x30_5 0.906757
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## x30_7 0.772268
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## x30_11 0.859655
## x30_12 0.810191
## x30_13 0.674082
## x30_14 0.767876
## x30_15 0.682508
## x30_16 NA
## x31_2 0.437616
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## x32_10 0.975577
## x32_11 0.057683 .
## x32_12 0.431380
## x32_13 0.072504 .
## x32_14 NA
## x32_16 NA
## x33_2 0.055504 .
## x33_3 0.016060 *
## x33_4 0.007118 **
## x33_5 0.052149 .
## x33_6 0.103128
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## x33_8 0.041110 *
## x33_9 0.029879 *
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## x33_12 0.00000088478977472 ***
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## x33_14 0.078083 .
## x33_15 0.028709 *
## x33_16 0.00008433746008687 ***
## x35_7 NA
## x35_8 NA
## x35_9 NA
## x35_16 NA
## x36_2 0.672835
## x36_3 0.489892
## x36_4 0.190885
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## x36_6 0.274044
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## x38_2 0.927902
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## x39_14 0.271734
## x39_15 0.031028 *
## x39_16 NA
## x40_2 0.970651
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## x40_12 0.200473
## x40_13 0.387580
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## x40_15 NA
## x40_16 NA
## x41_2 0.023746 *
## x41_3 0.036347 *
## x41_4 0.097081 .
## x41_5 0.085092 .
## x41_6 0.064256 .
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## x42_11 0.712307
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## x42_13 0.019038 *
## x42_14 0.259298
## x42_15 NA
## x42_16 NA
## x43_2 0.900198
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## x43_14 0.386999
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## x43_16 NA
## x44_2 0.872818
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## x47_7 0.844851
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## x47_10 0.213792
## x47_11 0.320886
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## x47_13 0.794676
## x47_14 NA
## x47_15 NA
## x47_16 NA
## x48_3 NA
## x48_7 0.933828
## x48_8 0.921365
## x48_9 NA
## x48_10 0.770030
## x48_11 NA
## x48_13 NA
## x48_14 NA
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## x49_2 0.695561
## x49_3 0.959286
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## x49_5 0.832803
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## x54_4 0.069393 .
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## x54_6 0.00000013390442709 ***
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## x54_10 0.00000000000000431 ***
## x54_11 0.00000370007131150 ***
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## x54_13 0.488555
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## x55_3 0.451955
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## x55_11 0.309259
## x55_12 0.261458
## x55_13 0.763879
## x55_14 NA
## x55_15 NA
## x55_16 NA
## x57_2 0.321076
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## x57_4 0.058094 .
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## x57_13 0.288550
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## x57_15 0.00003375062324133 ***
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## x58_5 0.562257
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## x60_12 NA
## x60_13 NA
## x60_14 NA
## x60_15 NA
## x60_16 NA
## x61_2 0.048009 *
## x61_3 0.496656
## x61_4 0.798095
## x61_5 0.927723
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## x63_3 0.00008365667368884 ***
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## x63_6 0.186931
## x63_7 0.296465
## x63_8 0.119722
## x63_9 0.302104
## x63_10 NA
## x63_11 NA
## x63_12 NA
## x63_13 NA
## x63_14 NA
## x63_15 NA
## x63_16 NA
## x64_2 0.340960
## x64_3 0.882583
## x64_4 0.161168
## x64_5 0.987592
## x64_6 0.950972
## x64_7 NA
## x64_8 NA
## x64_9 NA
## x64_10 NA
## x64_11 NA
## x64_12 NA
## x64_14 NA
## x64_16 NA
## x65_2 0.004842 **
## x65_3 0.350654
## x65_4 0.910573
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## x65_7 0.001957 **
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## x65_11 0.117438
## x65_12 0.00001784628053230 ***
## x65_13 0.661479
## x65_14 0.805708
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## x65_16 0.209286
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## x66_12 NA
## x66_13 0.358517
## x66_14 0.210398
## x66_15 0.151254
## x66_16 NA
## x68_14 NA
## x68_15 0.380141
## x68_16 NA
## x69_2 0.226700
## x69_3 0.104263
## x69_4 0.086779 .
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## x69_14 0.113552
## x69_15 NA
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## x70_2 0.094990 .
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## x70_4 NA
## x70_16 NA
## x71_11 NA
## x71_12 0.148763
## x71_13 0.073169 .
## x71_14 NA
## x71_15 NA
## x71_16 NA
## x73_2 0.823512
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## x73_13 0.405831
## x73_14 0.637508
## x73_15 NA
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## x76_2 0.296854
## x76_3 NA
## x76_4 NA
## x76_5 NA
## x76_6 NA
## x76_7 NA
## x76_8 NA
## x76_9 NA
## x76_10 NA
## x76_11 NA
## x76_12 NA
## x76_13 NA
## x76_14 NA
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## x77_3 NA
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## x77_16 NA
## x79_2 0.00000010520379803 ***
## x79_3 0.00000000107358863 ***
## x79_4 0.00000000038800235 ***
## x79_5 0.00000000019504685 ***
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## x79_13 0.00000000744529630 ***
## x79_14 0.00000003022474252 ***
## x79_15 0.00000000620893624 ***
## x79_16 0.000205 ***
## x80_10 NA
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## x81_12 0.539817
## x81_13 0.026678 *
## x81_15 NA
## x81_16 NA
## x84_2 NA
## x84_3 NA
## x84_4 NA
## x84_5 NA
## x84_6 NA
## x84_7 NA
## x84_8 NA
## x84_9 NA
## x84_10 NA
## x84_11 NA
## x84_12 NA
## x84_13 NA
## x84_14 NA
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## x84_16 NA
## x85_7 NA
## x85_12 NA
## x85_13 NA
## x85_14 NA
## x85_15 NA
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## x86_2 NA
## x86_3 0.773243
## x86_4 0.830053
## x86_5 0.858456
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## x86_7 NA
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## x86_16 NA
## x87_2 0.006157 **
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## x87_5 0.417183
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## x87_15 0.988147
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## x88_4 NA
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## x88_8 NA
## x88_9 NA
## x88_10 NA
## x88_11 NA
## x88_12 NA
## x88_13 NA
## x88_14 NA
## x88_16 NA
## x89_2 0.626298
## x89_3 0.637533
## x89_4 0.826057
## x89_5 0.861600
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## x96_10 0.873351
## x96_11 0.204228
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## x96_13 NA
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## x98_2 0.882141
## x98_3 0.848472
## x98_4 0.716218
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## x98_10 0.954758
## x98_11 0.910348
## x98_12 0.624043
## x98_13 0.562646
## x98_14 0.472430
## x98_15 0.732606
## x98_16 0.665720
## x99_2 0.310491
## x99_3 0.189580
## x99_4 0.085736 .
## x99_5 0.172526
## x99_6 0.166211
## x99_7 0.158400
## x99_8 0.155038
## x99_9 0.144957
## x99_10 0.152438
## x99_11 0.223369
## x99_12 0.296450
## x99_13 0.238968
## x99_14 0.248761
## x99_15 0.889413
## x99_16 0.852418
## x102_2 0.118056
## x102_3 0.810399
## x102_4 0.991737
## x102_5 0.094227 .
## x102_6 0.101205
## x102_7 0.089981 .
## x102_8 0.145904
## x102_9 0.122054
## x102_10 0.101627
## x102_11 0.086366 .
## x102_12 0.326351
## x102_13 0.386583
## x102_14 0.442838
## x102_15 0.765850
## x102_16 0.792680
## x103_3 0.055970 .
## x103_4 0.449787
## x103_5 0.420088
## x103_6 0.291802
## x103_7 0.283943
## x103_8 0.340369
## x103_9 0.356956
## x103_10 0.373724
## x103_11 0.303753
## x103_12 0.281259
## x103_13 0.330364
## x103_14 0.427516
## x103_15 0.097135 .
## x103_16 NA
## x104_16 0.000780 ***
## x106_2 0.005813 **
## x106_3 0.000146 ***
## x106_4 0.251041
## x106_5 0.485233
## x106_6 0.022109 *
## x106_7 0.011718 *
## x106_8 0.979491
## x106_9 0.436681
## x106_10 0.713238
## x106_11 0.745340
## x106_12 NA
## x106_13 0.00003063355772194 ***
## x106_14 NA
## x106_15 NA
## x106_16 0.937964
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 0.495 on 11222 degrees of freedom
## Multiple R-squared: 0.7922, Adjusted R-squared: 0.7165
## F-statistic: 10.45 on 4093 and 11222 DF, p-value: < 0.00000000000000022TrainSet_3$Val_pred <- predict(modelo3)
TrainSet_3$residuo <- resid(modelo3)
TrainSet_3$rp <- rstandard(modelo3)df_analise3 <- TrainSet_3 %>%
select(target, Val_pred, residuo, rp)# Erro quadratico medio na amostra de treino
mse3 <- mean((TrainSet_3$target - TrainSet_3$Val_pred)^2)
sqrt(mse3)## [1] 0.4237488Análise dos resíduos do modelo
plot(predict(modelo3),TrainSet_3$residuo, xlab = "Preditor linear",ylab = "Residuos")
abline(h = 0, lty = 2)
qqnorm(residuals(modelo3), ylab="Residuos",xlab="Quantis teoricos",main="")
qqline(residuals(modelo3))
##————————————————————————————— ## AMOSTRA DE VALIDACAO ##—————————————————————————————
# Função para detectar se uma coluna tem outliers
avaliacao_modelo <- function(dataset, predictions) {
# Calculando o MSE
mse <- mean((dataset$target - predictions)^2)
# Calculando o RMSE
rmse <- sqrt(mse)
# Calculando o MAE
mae <- mean(abs(dataset$target - predictions))
# Calcular a soma dos quadrados dos resíduos (SS_res)
SS_res <- sum((dataset$target - predictions)^2)
# Calcular a soma total dos quadrados (SS_tot)
SS_tot <- sum((dataset$target - mean(dataset$target))^2)
# Calcular o R² nos dados de validação
R2_validation <- 1 - (SS_res / SS_tot)
# Imprimindo os resultados
# Imprimir o R²
cat("R²:", R2_validation, "\n")
cat("MSE:", mse, "\n")
cat("RMSE:", rmse, "\n")
# cat("MAE:", mae, "\n")
}# Fazer previsões nos dados de validação
predictions <- predict(modelo_inicial, newdata = novo_ValidSet)## Warning in predict.lm(modelo_inicial, newdata = novo_ValidSet): prediction from
## rank-deficient fit; attr(*, "non-estim") has doubtful casespredictions1 <- predict(modelo1, newdata = novo_ValidSet)## Warning in predict.lm(modelo1, newdata = novo_ValidSet): prediction from
## rank-deficient fit; attr(*, "non-estim") has doubtful casespredictions2 <- predict(modelo2, newdata = novo_ValidSet)## Warning in predict.lm(modelo2, newdata = novo_ValidSet): prediction from
## rank-deficient fit; attr(*, "non-estim") has doubtful casespredictions3 <- predict(modelo3, newdata = novo_ValidSet)## Warning in predict.lm(modelo3, newdata = novo_ValidSet): prediction from
## rank-deficient fit; attr(*, "non-estim") has doubtful casessummary_modelo_inicial <- summary(modelo_inicial)
summary_modelo1 <- summary(modelo1)
summary_modelo2 <- summary(modelo2)
summary_modelo3 <- summary(modelo3)# Fazer previsões nos dados de validação
cat("\n","-----------Avaliação Modelo Inicial:-----------","\n",sep = "")##
## -----------Avaliação Modelo Inicial:-----------cat("\n","Treino:","\n",sep = "")##
## Treino:cat("R² ajustado:", summary_modelo_inicial$adj.r.squared, "\n")## R² ajustado: 0.4791807cat("R²:", summary_modelo_inicial$r.squared, "\n")## R²: 0.6034719cat("MSE:", mse, "\n")## MSE: 1.962061cat("RMSE:", sqrt(mse), "\n")## RMSE: 1.400736cat("\n","Validação:","\n",sep = "")##
## Validação:avaliacao_modelo(novo_ValidSet,predictions)## R²: 0.2911947
## MSE: 3.789938
## RMSE: 1.946776cat("\n","-----------Avaliação Modelo1:-----------","\n",sep = "")##
## -----------Avaliação Modelo1:-----------cat("\n","Treino:","\n",sep = "")##
## Treino:cat("R² ajustado:", summary_modelo1$adj.r.squared, "\n")## R² ajustado: 0.6157998cat("R²:", summary_modelo1$r.squared, "\n")## R²: 0.7091969cat("MSE:", mse1, "\n")## MSE: 0.5774865cat("RMSE:", sqrt(mse1), "\n")## RMSE: 0.7599253cat("\n","Validação:","\n",sep = "")##
## Validação:avaliacao_modelo(novo_ValidSet,predictions1)## R²: 0.3650671
## MSE: 3.394947
## RMSE: 1.842538cat("\n","-----------Avaliação Modelo2:-----------","\n",sep = "")##
## -----------Avaliação Modelo2:-----------cat("\n","Treino:","\n",sep = "")##
## Treino:cat("R² ajustado:", summary_modelo2$adj.r.squared, "\n")## R² ajustado: 0.6765441cat("R²:", summary_modelo2$r.squared, "\n")## R²: 0.7588375cat("MSE:", mse2, "\n")## MSE: 0.2911518cat("RMSE:", sqrt(mse2), "\n")## RMSE: 0.5395849cat("\n","Validação:","\n",sep = "")##
## Validação:avaliacao_modelo(novo_ValidSet,predictions2)## R²: 0.3395499
## MSE: 3.531386
## RMSE: 1.879198cat("\n","-----------Avaliação Modelo3:-----------","\n",sep = "")##
## -----------Avaliação Modelo3:-----------cat("\n","Treino:","\n",sep = "")##
## Treino:cat("R² ajustado:", summary_modelo3$adj.r.squared, "\n")## R² ajustado: 0.7164532cat("R²:", summary_modelo3$r.squared, "\n")## R²: 0.7922323cat("MSE:", mse3, "\n")## MSE: 0.179563cat("RMSE:", sqrt(mse3), "\n")## RMSE: 0.4237488cat("\n","Validação:","\n",sep = "")##
## Validação:avaliacao_modelo(novo_ValidSet,predictions3)## R²: 0.3072821
## MSE: 3.70392
## RMSE: 1.924557